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simplify sections
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@ -88,6 +88,11 @@ objects. This depends on the return type of the [model](#models).
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| `responses` | The generated prompts. ~~Iterable[Any]~~ |
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| **RETURNS** | The annotated documents. ~~Iterable[Doc]~~ |
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### Summarization {id="summarization"}
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A summarization task takes a document as input and generates a summary that is
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stored in an extension attribute.
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#### spacy.Summarization.v1 {id="summarization-v1"}
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The `spacy.Summarization.v1` task supports both zero-shot and few-shot
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@ -154,9 +159,9 @@ The NER task identifies non-overlapping entities in text.
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#### spacy.NER.v2 {id="ner-v2"}
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The built-in NER task supports both zero-shot and few-shot prompting. This
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version also supports explicitly defining the provided labels with custom
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descriptions.
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This version supports explicitly defining the provided labels with custom
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descriptions, and further supports zero-shot and few-shot prompting just like
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v1.
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> #### Example config
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>
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@ -182,15 +187,6 @@ The parameters `alignment_mode`, `case_sensitive_matching` and `single_match`
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are identical to the [v1](#ner-v1) implementation. The format of few-shot
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examples are also the same.
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```ini
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[components.llm.task]
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@llm_tasks = "spacy.NER.v2"
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labels = PERSON,ORGANISATION,LOCATION
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[components.llm.task.examples]
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@misc = "spacy.FewShotReader.v1"
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path = "ner_examples.yml"
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```
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> Label descriptions can also be used with explicit examples to give as much
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> info to the LLM model as possible.
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@ -273,18 +269,19 @@ supports `.yml`, `.yaml`, `.json` and `.jsonl`.
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```
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```ini
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[components.llm.task]
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@llm_tasks = "spacy.NER.v1"
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labels = PERSON,ORGANISATION,LOCATION
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[components.llm.task.examples]
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@misc = "spacy.FewShotReader.v1"
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path = "ner_examples.yml"
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```
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### SpanCat {id="spancat"}
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The SpanCat task identifies potentially overlapping entities in text.
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#### spacy.SpanCat.v2 {id="spancat-v2"}
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The built-in SpanCat task is a simple adaptation of the NER task to support
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overlapping entities and store its annotations in `doc.spans`.
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The built-in SpanCat v2 task is a simple adaptation of the NER v2 task to
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support overlapping entities and store its annotations in `doc.spans`.
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> #### Example config
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>
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@ -307,8 +304,9 @@ overlapping entities and store its annotations in `doc.spans`.
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| `case_sensitive_matching` | Whether to search without case sensitivity. Defaults to `False`. ~~bool~~ |
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| `single_match` | Whether to match an entity in the LLM's response only once (the first hit) or multiple times. Defaults to `False`. ~~bool~~ |
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Except for the `spans_key` parameter, the SpanCat task reuses the configuration
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from the NER task. Refer to [its documentation](#ner-v2) for more insight.
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Except for the `spans_key` parameter, the SpanCat v2 task reuses the
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configuration from the NER v2 task. Refer to [its documentation](#ner-v2) for
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more insight.
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#### spacy.SpanCat.v1 {id="spancat-v1"}
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@ -335,14 +333,19 @@ v1 NER task to support overlapping entities and store its annotations in
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| `case_sensitive_matching` | Whether to search without case sensitivity. Defaults to `False`. ~~bool~~ |
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| `single_match` | Whether to match an entity in the LLM's response only once (the first hit) or multiple times. Defaults to `False`. ~~bool~~ |
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Except for the `spans_key` parameter, the SpanCat task reuses the configuration
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from the NER task. Refer to [its documentation](#ner-v1) for more insight.
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Except for the `spans_key` parameter, the SpanCat v1 task reuses the
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configuration from the NER v1 task. Refer to [its documentation](#ner-v1) for
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more insight.
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### TextCat {id="textcat"}
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The TextCat task labels documents with relevant categories.
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#### spacy.TextCat.v3 {id="textcat-v3"}
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Version 3 (the most recent) of the built-in TextCat task supports both zero-shot
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and few-shot prompting. It allows setting definitions of labels. Those
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definitions are included in the prompt.
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On top of the functionality from v2, version 3 of the built-in TextCat tasks
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allows setting definitions of labels. Those definitions are included in the
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prompt.
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> #### Example config
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>
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@ -357,52 +360,23 @@ definitions are included in the prompt.
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> examples = null
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> ```
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| Argument | Description |
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| ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `labels` | List of labels or str of comma-separated list of labels. ~~Union[List[str], str]~~ |
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| `label_definitions` | Dictionary of label definitions. Included in the prompt, if set. Defaults to `None`. ~~Optional[Dict[str, str]]~~ |
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| `template` | Custom prompt template to send to LLM model. Default templates for each task are located in the `spacy_llm/tasks/templates` directory. Defaults to [`textcat.v3.jinja`](https://github.com/explosion/spacy-llm/blob/main/spacy_llm/tasks/templates/textcat.v3.jinja). ~~str~~ |
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| `examples` | Optional function that generates examples for few-shot learning. Defaults to `None`. ~~Optional[Callable[[], Iterable[Any]]]~~ |
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| `normalizer` | Function that normalizes the labels as returned by the LLM. If `None`, falls back to `spacy.LowercaseNormalizer.v1`. Defaults to `None`. ~~Optional[Callable[[str], str]]~~ |
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| `exclusive_classes` | If set to `True`, only one label per document should be valid. If set to `False`, one document can have multiple labels. Defaults to `False`. ~~bool~~ |
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| `allow_none` | When set to `True`, allows the LLM to not return any of the given label. The resulting dict in `doc.cats` will have `0.0` scores for all labels. Defaults to `True`. ~~bool~~ |
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| `verbose` | If set to `True`, warnings will be generated when the LLM returns invalid responses. Defaults to `False`. ~~bool~~ |
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| Argument | Description |
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| ------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `labels` | List of labels or str of comma-separated list of labels. ~~Union[List[str], str]~~ |
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| `label_definitions` (NEW) | Dictionary of label definitions. Included in the prompt, if set. Defaults to `None`. ~~Optional[Dict[str, str]]~~ |
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| `template` | Custom prompt template to send to LLM model. Default templates for each task are located in the `spacy_llm/tasks/templates` directory. Defaults to [`textcat.v3.jinja`](https://github.com/explosion/spacy-llm/blob/main/spacy_llm/tasks/templates/textcat.v3.jinja). ~~str~~ |
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| `examples` | Optional function that generates examples for few-shot learning. Defaults to `None`. ~~Optional[Callable[[], Iterable[Any]]]~~ |
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| `normalizer` | Function that normalizes the labels as returned by the LLM. If `None`, falls back to `spacy.LowercaseNormalizer.v1`. Defaults to `None`. ~~Optional[Callable[[str], str]]~~ |
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| `exclusive_classes` | If set to `True`, only one label per document should be valid. If set to `False`, one document can have multiple labels. Defaults to `False`. ~~bool~~ |
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| `allow_none` | When set to `True`, allows the LLM to not return any of the given label. The resulting dict in `doc.cats` will have `0.0` scores for all labels. Defaults to `True`. ~~bool~~ |
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| `verbose` | If set to `True`, warnings will be generated when the LLM returns invalid responses. Defaults to `False`. ~~bool~~ |
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To perform [few-shot learning](/usage/large-langauge-models#few-shot-prompts),
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you can write down a few examples in a separate file, and provide these to be
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injected into the prompt to the LLM. The default reader `spacy.FewShotReader.v1`
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supports `.yml`, `.yaml`, `.json` and `.jsonl`.
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```json
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[
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{
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"text": "You look great!",
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"answer": "Compliment"
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},
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{
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"text": "You are not very clever at all.",
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"answer": "Insult"
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}
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]
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```
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```ini
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[components.llm.task]
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@llm_tasks = "spacy.TextCat.v3"
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labels = ["COMPLIMENT", "INSULT"]
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label_definitions = {
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"COMPLIMENT": "a polite expression of praise or admiration.",
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"INSULT": "a disrespectful or scornfully abusive remark or act."
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}
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[components.llm.task.examples]
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@misc = "spacy.FewShotReader.v1"
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path = "textcat_examples.json"
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```
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The formatting of few-shot examples is the same as those for the
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[v1](#textcat-v1) implementation.
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#### spacy.TextCat.v2 {id="textcat-v2"}
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Version 2 of the built-in TextCat task supports both zero-shot and few-shot
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prompting and includes an improved prompt template.
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V2 includes all v1 functionality, with an improved prompt template.
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> #### Example config
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>
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@ -423,32 +397,8 @@ prompting and includes an improved prompt template.
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| `allow_none` | When set to `True`, allows the LLM to not return any of the given label. The resulting dict in `doc.cats` will have `0.0` scores for all labels. Defaults to `True`. ~~bool~~ |
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| `verbose` | If set to `True`, warnings will be generated when the LLM returns invalid responses. Defaults to `False`. ~~bool~~ |
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To perform [few-shot learning](/usage/large-langauge-models#few-shot-prompts),
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you can write down a few examples in a separate file, and provide these to be
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injected into the prompt to the LLM. The default reader `spacy.FewShotReader.v1`
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supports `.yml`, `.yaml`, `.json` and `.jsonl`.
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```json
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[
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{
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"text": "You look great!",
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"answer": "Compliment"
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},
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{
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"text": "You are not very clever at all.",
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"answer": "Insult"
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}
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]
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```
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```ini
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[components.llm.task]
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@llm_tasks = "spacy.TextCat.v2"
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labels = ["COMPLIMENT", "INSULT"]
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[components.llm.task.examples]
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@misc = "spacy.FewShotReader.v1"
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path = "textcat_examples.json"
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```
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The formatting of few-shot examples is the same as those for the
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[v1](#textcat-v1) implementation.
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#### spacy.TextCat.v1 {id="textcat-v1"}
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@ -492,14 +442,15 @@ supports `.yml`, `.yaml`, `.json` and `.jsonl`.
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```
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```ini
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[components.llm.task]
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@llm_tasks = "spacy.TextCat.v2"
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labels = COMPLIMENT,INSULT
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[components.llm.task.examples]
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@misc = "spacy.FewShotReader.v1"
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path = "textcat_examples.json"
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```
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### REL {id="rel"}
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The REL task extracts relations between named entities.
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#### spacy.REL.v1 {id="rel-v1"}
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The built-in REL task supports both zero-shot and few-shot prompting. It relies
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@ -545,10 +496,14 @@ Note: the REL task relies on pre-extracted entities to make its prediction.
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Hence, you'll need to add a component that populates `doc.ents` with recognized
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spans to your spaCy pipeline and put it _before_ the REL component.
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### Lemma {id="lemma"}
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The Lemma task lemmatizes the provided text and updates the `lemma_` attribute
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in the doc's tokens accordingly.
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#### spacy.Lemma.v1 {id="lemma-v1"}
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The `Lemma.v1` task lemmatizes the provided text and updates the `lemma_`
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attribute in the doc's tokens accordingly.
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This task supports both zero-shot and few-shot prompting.
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> #### Example config
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>
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@ -563,9 +518,9 @@ attribute in the doc's tokens accordingly.
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| `template` | Custom prompt template to send to LLM model. Default templates for each task are located in the `spacy_llm/tasks/templates` directory. Defaults to [lemma.v1.jinja](https://github.com/explosion/spacy-llm/blob/main/spacy_llm/tasks/templates/lemma.v1.jinja). ~~str~~ |
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| `examples` | Optional function that generates examples for few-shot learning. Defaults to `None`. ~~Optional[Callable[[], Iterable[Any]]]~~ |
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`Lemma.v1` prompts the LLM to lemmatize the passed text and return the
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lemmatized version as a list of tokens and their corresponding lemma. E. g. the
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text `I'm buying ice cream for my friends` should invoke the response
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The task prompts the LLM to lemmatize the passed text and return the lemmatized
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version as a list of tokens and their corresponding lemma. E. g. the text
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`I'm buying ice cream for my friends` should invoke the response
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```
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I: I
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@ -617,12 +572,16 @@ supports `.yml`, `.yaml`, `.json` and `.jsonl`.
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path = "lemma_examples.yml"
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```
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#### spacy.Sentiment.v1 {id="sentiment-v1"}
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### Sentiment {id="sentiment"}
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Performs sentiment analysis on provided texts. Scores between 0 and 1 are stored
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in `Doc._.sentiment` - the higher, the more positive. Note in cases of parsing
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issues (e. g. in case of unexpected LLM responses) the value might be `None`.
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#### spacy.Sentiment.v1 {id="sentiment-v1"}
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This task supports both zero-shot and few-shot prompting.
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> #### Example config
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>
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> ```ini
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@ -661,6 +620,11 @@ supports `.yml`, `.yaml`, `.json` and `.jsonl`.
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path = "sentiment_examples.yml"
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```
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### NoOp {id="noop"}
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This task is only useful for testing - it tells the LLM to do nothing, and does
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not set any fields on the `docs`.
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#### spacy.NoOp.v1 {id="noop-v1"}
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> #### Example config
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@ -670,10 +634,7 @@ path = "sentiment_examples.yml"
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> @llm_tasks = "spacy.NoOp.v1"
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> ```
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This task is only useful for testing - it tells the LLM to do nothing, and does
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not set any fields on the `docs`.
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### Models {id="models"}
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## Models {id="models"}
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A _model_ defines which LLM model to query, and how to query it. It can be a
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simple function taking a collection of prompts (consistent with the output type
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@ -683,7 +644,7 @@ it's a function of type `Callable[[Iterable[Any]], Iterable[Any]]`, but specific
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implementations can have other signatures, like
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`Callable[[Iterable[str]], Iterable[str]]`.
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#### API Keys {id="api-keys"}
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### API Keys {id="api-keys"}
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Note that when using hosted services, you have to ensure that the proper API
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keys are set as environment variables as described by the corresponding
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@ -709,10 +670,12 @@ and for Anthropic
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export ANTHROPIC_API_KEY="..."
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```
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#### spacy.GPT-4.v1 {id="gpt-4"}
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### GPT-4 {id="gpt-4"}
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OpenAI's `gpt-4` model family.
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#### spacy.GPT-4.v1 {id="gpt-4-v1"}
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> #### Example config:
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>
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> ```ini
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@ -730,10 +693,12 @@ OpenAI's `gpt-4` model family.
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| `max_tries` | Max. number of tries for API request. Defaults to `3`. ~~int~~ |
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| `timeout` | Timeout for API request in seconds. Defaults to `30`. ~~int~~ |
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#### spacy.GPT-3-5.v1 {id="gpt-3-5"}
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### GPT-3-5 {id="gpt-3-5"}
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OpenAI's `gpt-3-5` model family.
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#### spacy.GPT-3-5.v1 {id="gpt-3-5-v1"}
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> #### Example config
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>
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> ```ini
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@ -751,10 +716,12 @@ OpenAI's `gpt-3-5` model family.
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| `max_tries` | Max. number of tries for API request. Defaults to `3`. ~~int~~ |
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| `timeout` | Timeout for API request in seconds. Defaults to `30`. ~~int~~ |
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#### spacy.Text-Davinci.v1 {id="text-davinci"}
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### Text-Davinci {id="text-davinci"}
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OpenAI's `text-davinci` model family.
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#### spacy.Text-Davinci.v1 {id="text-davinci-v1"}
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> #### Example config
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>
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> ```ini
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@ -772,10 +739,12 @@ OpenAI's `text-davinci` model family.
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| `max_tries` | Max. number of tries for API request. Defaults to `3`. ~~int~~ |
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| `timeout` | Timeout for API request in seconds. Defaults to `30`. ~~int~~ |
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#### spacy.Code-Davinci.v1 {id="code-davinci"}
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### Code-Davinci {id="code-davinci"}
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OpenAI's `code-davinci` model family.
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#### spacy.Code-Davinci.v1 {id="code-davinci-v1"}
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> #### Example config
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>
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> ```ini
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@ -793,10 +762,12 @@ OpenAI's `code-davinci` model family.
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| `max_tries` | Max. number of tries for API request. Defaults to `3`. ~~int~~ |
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| `timeout` | Timeout for API request in seconds. Defaults to `30`. ~~int~~ |
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#### spacy.Text-Curie.v1 {id="text-curie"}
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### Text-Curie {id="text-curie"}
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OpenAI's `text-curie` model family.
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#### spacy.Text-Curie.v1 {id="text-curie-v1"}
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> #### Example config
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>
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> ```ini
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@ -814,10 +785,12 @@ OpenAI's `text-curie` model family.
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| `max_tries` | Max. number of tries for API request. Defaults to `3`. ~~int~~ |
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| `timeout` | Timeout for API request in seconds. Defaults to `30`. ~~int~~ |
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#### spacy.Text-Babbage.v1 {id="text-babbage"}
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### Text-Babbage {id="text-babbage"}
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OpenAI's `text-babbage` model family.
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#### spacy.Text-Babbage.v1 {id="text-babbage-v1"}
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> #### Example config
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>
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> ```ini
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@ -835,10 +808,12 @@ OpenAI's `text-babbage` model family.
|
|||
| `max_tries` | Max. number of tries for API request. Defaults to `3`. ~~int~~ |
|
||||
| `timeout` | Timeout for API request in seconds. Defaults to `30`. ~~int~~ |
|
||||
|
||||
#### spacy.Text-Ada.v1 {id="text-ada"}
|
||||
### Text-Ada {id="text-ada"}
|
||||
|
||||
OpenAI's `text-ada` model family.
|
||||
|
||||
#### spacy.Text-Ada.v1 {id="text-ada-v1"}
|
||||
|
||||
> #### Example config
|
||||
>
|
||||
> ```ini
|
||||
|
|
@ -856,10 +831,12 @@ OpenAI's `text-ada` model family.
|
|||
| `max_tries` | Max. number of tries for API request. Defaults to `3`. ~~int~~ |
|
||||
| `timeout` | Timeout for API request in seconds. Defaults to `30`. ~~int~~ |
|
||||
|
||||
#### spacy.Davinci.v1 {id="davinci"}
|
||||
### Davinci {id="davinci"}
|
||||
|
||||
OpenAI's `davinci` model family.
|
||||
|
||||
#### spacy.Davinci.v1 {id="davinci-v1"}
|
||||
|
||||
> #### Example config
|
||||
>
|
||||
> ```ini
|
||||
|
|
@ -877,10 +854,12 @@ OpenAI's `davinci` model family.
|
|||
| `max_tries` | Max. number of tries for API request. Defaults to `3`. ~~int~~ |
|
||||
| `timeout` | Timeout for API request in seconds. Defaults to `30`. ~~int~~ |
|
||||
|
||||
#### spacy.Curie.v1 {id="curie"}
|
||||
### Curie {id="curie"}
|
||||
|
||||
OpenAI's `curie` model family.
|
||||
|
||||
#### spacy.Curie.v1 {id="curie-v1"}
|
||||
|
||||
> #### Example config
|
||||
>
|
||||
> ```ini
|
||||
|
|
@ -898,10 +877,12 @@ OpenAI's `curie` model family.
|
|||
| `max_tries` | Max. number of tries for API request. Defaults to `3`. ~~int~~ |
|
||||
| `timeout` | Timeout for API request in seconds. Defaults to `30`. ~~int~~ |
|
||||
|
||||
#### spacy.Babbage.v1 {id="babbage"}
|
||||
### Babbage {id="babbage"}
|
||||
|
||||
OpenAI's `babbage` model family.
|
||||
|
||||
#### spacy.Babbage.v1 {id="babbage-v1"}
|
||||
|
||||
> #### Example config
|
||||
>
|
||||
> ```ini
|
||||
|
|
@ -919,10 +900,12 @@ OpenAI's `babbage` model family.
|
|||
| `max_tries` | Max. number of tries for API request. Defaults to `3`. ~~int~~ |
|
||||
| `timeout` | Timeout for API request in seconds. Defaults to `30`. ~~int~~ |
|
||||
|
||||
#### spacy.Ada.v1 {id="ada"}
|
||||
### Ada {id="ada"}
|
||||
|
||||
OpenAI's `ada` model family.
|
||||
|
||||
#### spacy.Ada.v1 {id="ada-v1"}
|
||||
|
||||
> #### Example config
|
||||
>
|
||||
> ```ini
|
||||
|
|
@ -940,10 +923,12 @@ OpenAI's `ada` model family.
|
|||
| `max_tries` | Max. number of tries for API request. Defaults to `3`. ~~int~~ |
|
||||
| `timeout` | Timeout for API request in seconds. Defaults to `30`. ~~int~~ |
|
||||
|
||||
#### spacy.Command.v1 {id="command"}
|
||||
### Command {id="command"}
|
||||
|
||||
Cohere's `command` model family.
|
||||
|
||||
#### spacy.Command.v1 {id="command-v1"}
|
||||
|
||||
> #### Example config
|
||||
>
|
||||
> ```ini
|
||||
|
|
@ -961,10 +946,12 @@ Cohere's `command` model family.
|
|||
| `max_tries` | Max. number of tries for API request. Defaults to `3`. ~~int~~ |
|
||||
| `timeout` | Timeout for API request in seconds. Defaults to `30`. ~~int~~ |
|
||||
|
||||
#### spacy.Claude-2.v1 {id="claude-2"}
|
||||
### Claude-2 {id="claude-2"}
|
||||
|
||||
Anthropic's `claude-2` model family.
|
||||
|
||||
#### spacy.Claude-2.v1 {id="claude-2-v1"}
|
||||
|
||||
> #### Example config
|
||||
>
|
||||
> ```ini
|
||||
|
|
@ -982,10 +969,12 @@ Anthropic's `claude-2` model family.
|
|||
| `max_tries` | Max. number of tries for API request. Defaults to `3`. ~~int~~ |
|
||||
| `timeout` | Timeout for API request in seconds. Defaults to `30`. ~~int~~ |
|
||||
|
||||
#### spacy.Claude-1.v1 {id="claude-1"}
|
||||
### Claude-1 {id="claude-1"}
|
||||
|
||||
Anthropic's `claude-1` model family.
|
||||
|
||||
#### spacy.Claude-1.v1 {id="claude-1-v1"}
|
||||
|
||||
> #### Example config
|
||||
>
|
||||
> ```ini
|
||||
|
|
@ -1003,10 +992,12 @@ Anthropic's `claude-1` model family.
|
|||
| `max_tries` | Max. number of tries for API request. Defaults to `3`. ~~int~~ |
|
||||
| `timeout` | Timeout for API request in seconds. Defaults to `30`. ~~int~~ |
|
||||
|
||||
#### spacy.Claude-instant-1.v1 {id="claude-instant-1"}
|
||||
### Claude-instant-1 {id="claude-instant-1"}
|
||||
|
||||
Anthropic's `claude-instant-1` model family.
|
||||
|
||||
#### spacy.Claude-instant-1.v1 {id="claude-instant-1-v1"}
|
||||
|
||||
> #### Example config
|
||||
>
|
||||
> ```ini
|
||||
|
|
@ -1024,10 +1015,12 @@ Anthropic's `claude-instant-1` model family.
|
|||
| `max_tries` | Max. number of tries for API request. Defaults to `3`. ~~int~~ |
|
||||
| `timeout` | Timeout for API request in seconds. Defaults to `30`. ~~int~~ |
|
||||
|
||||
#### spacy.Claude-instant-1-1.v1 {id="claude-instant-1-1"}
|
||||
### Claude-instant-1-1 {id="claude-instant-1-1"}
|
||||
|
||||
Anthropic's `claude-instant-1.1` model family.
|
||||
|
||||
#### spacy.Claude-instant-1-1.v1 {id="claude-instant-1-1-v1"}
|
||||
|
||||
> #### Example config
|
||||
>
|
||||
> ```ini
|
||||
|
|
@ -1045,10 +1038,12 @@ Anthropic's `claude-instant-1.1` model family.
|
|||
| `max_tries` | Max. number of tries for API request. Defaults to `3`. ~~int~~ |
|
||||
| `timeout` | Timeout for API request in seconds. Defaults to `30`. ~~int~~ |
|
||||
|
||||
#### spacy.Claude-1-0.v1 {id="claude-1-0"}
|
||||
#### Claude-1-0 {id="claude-1-0"}
|
||||
|
||||
Anthropic's `claude-1.0` model family.
|
||||
|
||||
#### spacy.Claude-1-0.v1 {id="claude-1-0-v1"}
|
||||
|
||||
> #### Example config
|
||||
>
|
||||
> ```ini
|
||||
|
|
@ -1066,10 +1061,12 @@ Anthropic's `claude-1.0` model family.
|
|||
| `max_tries` | Max. number of tries for API request. Defaults to `3`. ~~int~~ |
|
||||
| `timeout` | Timeout for API request in seconds. Defaults to `30`. ~~int~~ |
|
||||
|
||||
#### spacy.Claude-1-2.v1 {id="claude-1-2"}
|
||||
#### Claude-1-2 {id="claude-1-2"}
|
||||
|
||||
Anthropic's `claude-1.2` model family.
|
||||
|
||||
#### spacy.Claude-1-2.v1 {id="claude-1-2-v1"}
|
||||
|
||||
> #### Example config
|
||||
>
|
||||
> ```ini
|
||||
|
|
@ -1087,10 +1084,12 @@ Anthropic's `claude-1.2` model family.
|
|||
| `max_tries` | Max. number of tries for API request. Defaults to `3`. ~~int~~ |
|
||||
| `timeout` | Timeout for API request in seconds. Defaults to `30`. ~~int~~ |
|
||||
|
||||
#### spacy.Claude-1-3.v1 {id="claude-1-3"}
|
||||
#### Claude-1-3 {id="claude-1-3"}
|
||||
|
||||
Anthropic's `claude-1.3` model family.
|
||||
|
||||
#### spacy.Claude-1-3.v1 {id="claude-1-3-v1"}
|
||||
|
||||
> #### Example config
|
||||
>
|
||||
> ```ini
|
||||
|
|
@ -1108,7 +1107,11 @@ Anthropic's `claude-1.3` model family.
|
|||
| `max_tries` | Max. number of tries for API request. Defaults to `3`. ~~int~~ |
|
||||
| `timeout` | Timeout for API request in seconds. Defaults to `30`. ~~int~~ |
|
||||
|
||||
#### spacy.Dolly.v1 {id="dolly"}
|
||||
### Dolly {id="dolly"}
|
||||
|
||||
Databrick's open-source `Dolly` model family.
|
||||
|
||||
#### spacy.Dolly.v1 {id="dolly-v1"}
|
||||
|
||||
To use this model, ideally you have a GPU enabled and have installed
|
||||
`transformers`, `torch` and CUDA in your virtual environment. This allows you to
|
||||
|
|
@ -1157,7 +1160,11 @@ can
|
|||
[define the cached directory](https://huggingface.co/docs/huggingface_hub/main/en/guides/manage-cache)
|
||||
by setting the environmental variable `HF_HOME`.
|
||||
|
||||
#### spacy.Llama2.v1 {id="llama2"}
|
||||
### Llama2 {id="llama2"}
|
||||
|
||||
Meta AI's open-source `Llama2` model family.
|
||||
|
||||
#### spacy.Llama2.v1 {id="llama2-v1"}
|
||||
|
||||
To use this model, ideally you have a GPU enabled and have installed
|
||||
`transformers`, `torch` and CUDA in your virtual environment. This allows you to
|
||||
|
|
@ -1203,7 +1210,11 @@ can
|
|||
[define the cache directory](https://huggingface.co/docs/huggingface_hub/main/en/guides/manage-cache)
|
||||
by setting the environmental variable `HF_HOME`.
|
||||
|
||||
#### spacy.Falcon.v1 {id="falcon"}
|
||||
### Falcon {id="falcon"}
|
||||
|
||||
TII's open-source `Falcon` model family.
|
||||
|
||||
#### spacy.Falcon.v1 {id="falcon-v1"}
|
||||
|
||||
To use this model, ideally you have a GPU enabled and have installed
|
||||
`transformers`, `torch` and CUDA in your virtual environment. This allows you to
|
||||
|
|
@ -1244,7 +1255,11 @@ can
|
|||
[define the cache directory](https://huggingface.co/docs/huggingface_hub/main/en/guides/manage-cache)
|
||||
by setting the environmental variable `HF_HOME`.
|
||||
|
||||
#### spacy.StableLM.v1 {id="stablelm"}
|
||||
### StableLM {id="stablelm"}
|
||||
|
||||
Stability AI's open-source `StableLM` model family.
|
||||
|
||||
#### spacy.StableLM.v1 {id="stablelm-v1"}
|
||||
|
||||
To use this model, ideally you have a GPU enabled and have installed
|
||||
`transformers`, `torch` and CUDA in your virtual environment.
|
||||
|
|
@ -1287,7 +1302,11 @@ can
|
|||
[define the cached directory](https://huggingface.co/docs/huggingface_hub/main/en/guides/manage-cache)
|
||||
by setting the environmental variable `HF_HOME`.
|
||||
|
||||
#### spacy.OpenLLaMA.v1 {id="openllama"}
|
||||
### OpenLLaMA {id="openllama"}
|
||||
|
||||
OpenLM Research's open-source `OpenLLaMA` model family.
|
||||
|
||||
#### spacy.OpenLLaMA.v1 {id="openllama-v1"}
|
||||
|
||||
To use this model, ideally you have a GPU enabled and have installed
|
||||
|
||||
|
|
@ -1333,7 +1352,7 @@ can
|
|||
[define the cached directory](https://huggingface.co/docs/huggingface_hub/main/en/guides/manage-cache)
|
||||
by setting the environmental variable `HF_HOME`.
|
||||
|
||||
#### LangChain models {id="langchain-models"}
|
||||
### LangChain models {id="langchain-models"}
|
||||
|
||||
To use [LangChain](https://github.com/hwchase17/langchain) for the API retrieval
|
||||
part, make sure you have installed it first:
|
||||
|
|
@ -1374,7 +1393,7 @@ The name of the model to be used has to be passed in via the `name` attribute.
|
|||
The default `query` (`spacy.CallLangChain.v1`) executes the prompts by running
|
||||
`model(text)` for each given textual prompt.
|
||||
|
||||
### Cache {id="cache"}
|
||||
## Cache {id="cache"}
|
||||
|
||||
Interacting with LLMs, either through an external API or a local instance, is
|
||||
costly. Since developing an NLP pipeline generally means a lot of exploration
|
||||
|
|
@ -1406,9 +1425,9 @@ provide your own registered function returning your own cache implementation. If
|
|||
you wish to do so, ensure that your cache object adheres to the `Protocol`
|
||||
defined in `spacy_llm.ty.Cache`.
|
||||
|
||||
### Various functions {id="various-functions"}
|
||||
## Various functions {id="various-functions"}
|
||||
|
||||
#### spacy.FewShotReader.v1 {id="fewshotreader-v1"}
|
||||
### spacy.FewShotReader.v1 {id="fewshotreader-v1"}
|
||||
|
||||
This function is registered in spaCy's `misc` registry, and reads in examples
|
||||
from a `.yml`, `.yaml`, `.json` or `.jsonl` file. It uses
|
||||
|
|
@ -1427,7 +1446,7 @@ them depending on the file extension.
|
|||
| -------- | ----------------------------------------------------------------------------------------------- |
|
||||
| `path` | Path to an examples file with suffix `.yml`, `.yaml`, `.json` or `.jsonl`. ~~Union[str, Path]~~ |
|
||||
|
||||
#### spacy.FileReader.v1 {id="filereader-v1"}
|
||||
### spacy.FileReader.v1 {id="filereader-v1"}
|
||||
|
||||
This function is registered in spaCy's `misc` registry, and reads a file
|
||||
provided to the `path` to return a `str` representation of its contents. This
|
||||
|
|
@ -1447,7 +1466,7 @@ template.
|
|||
| -------- | ------------------------------------------------- |
|
||||
| `path` | Path to the file to be read. ~~Union[str, Path]~~ |
|
||||
|
||||
#### Normalizer functions {id="normalizer-functions"}
|
||||
### Normalizer functions {id="normalizer-functions"}
|
||||
|
||||
These functions provide simple normalizations for string comparisons, e.g.
|
||||
between a list of specified labels and a label given in the raw text of the LLM
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user