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Update API and usage pages w.r.t. model registry refactoring.
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Raphael Mitsch
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@ -1477,20 +1477,21 @@ These models all take the same parameters:
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>
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> ```ini
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> [components.llm.model]
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> @llm_models = "spacy.Llama2.v1"
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> @llm_models = "spacy.HF.v1"
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> name = "Llama-2-7b-hf"
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> ```
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Currently, these models are provided as part of the core library:
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Currently, these models are provided as part of the core library (more models
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can be accessed through the `langchain` integration):
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| Model | Provider | Supported names | HF directory |
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| -------------------- | --------------- | ------------------------------------------------------------------------------------------------------------ | -------------------------------------- |
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| `spacy.Dolly.v1` | Databricks | `["dolly-v2-3b", "dolly-v2-7b", "dolly-v2-12b"]` | https://huggingface.co/databricks |
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| `spacy.Falcon.v1` | TII | `["falcon-rw-1b", "falcon-7b", "falcon-7b-instruct", "falcon-40b-instruct"]` | https://huggingface.co/tiiuae |
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| `spacy.Llama2.v1` | Meta AI | `["Llama-2-7b-hf", "Llama-2-13b-hf", "Llama-2-70b-hf"]` | https://huggingface.co/meta-llama |
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| `spacy.Mistral.v1` | Mistral AI | `["Mistral-7B-v0.1", "Mistral-7B-Instruct-v0.1"]` | https://huggingface.co/mistralai |
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| `spacy.StableLM.v1` | Stability AI | `["stablelm-base-alpha-3b", "stablelm-base-alpha-7b", "stablelm-tuned-alpha-3b", "stablelm-tuned-alpha-7b"]` | https://huggingface.co/stabilityai |
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| `spacy.OpenLLaMA.v1` | OpenLM Research | `["open_llama_3b", "open_llama_7b", "open_llama_7b_v2", "open_llama_13b"]` | https://huggingface.co/openlm-research |
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| Model family | Author | Names of available model | HF directory |
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| ------------ | --------------- | ------------------------------------------------------------------------------------------------------------ | -------------------------------------- |
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| Dolly | Databricks | `["dolly-v2-3b", "dolly-v2-7b", "dolly-v2-12b"]` | https://huggingface.co/databricks |
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| Falcon | TII | `["falcon-rw-1b", "falcon-7b", "falcon-7b-instruct", "falcon-40b-instruct"]` | https://huggingface.co/tiiuae |
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| Llama 2 | Meta AI | `["Llama-2-7b-hf", "Llama-2-13b-hf", "Llama-2-70b-hf"]` | https://huggingface.co/meta-llama |
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| Mistral | Mistral AI | `["Mistral-7B-v0.1", "Mistral-7B-Instruct-v0.1"]` | https://huggingface.co/mistralai |
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| Stable LM | Stability AI | `["stablelm-base-alpha-3b", "stablelm-base-alpha-7b", "stablelm-tuned-alpha-3b", "stablelm-tuned-alpha-7b"]` | https://huggingface.co/stabilityai |
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| OpenLLaMa | OpenLM Research | `["open_llama_3b", "open_llama_7b", "open_llama_7b_v2", "open_llama_13b"]` | https://huggingface.co/openlm-research |
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<Infobox variant="warning" title="Gated models on Hugging Face" id="hf_licensing">
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@ -1540,7 +1541,7 @@ To use [LangChain](https://github.com/hwchase17/langchain) for the API retrieval
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part, make sure you have installed it first:
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```shell
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python -m pip install "langchain==0.0.191"
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python -m pip install "langchain>=0.1,<0.2"
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# Or install with spacy-llm directly
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python -m pip install "spacy-llm[extras]"
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```
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@ -1550,9 +1551,12 @@ Note that LangChain currently only supports Python 3.9 and beyond.
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LangChain models in `spacy-llm` work slightly differently. `langchain`'s models
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are parsed automatically, each LLM class in `langchain` has one entry in
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`spacy-llm`'s registry. As `langchain`'s design has one class per API and not
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per model, this results in registry entries like `langchain.OpenAI.v1` - i. e.
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there is one registry entry per API and not per model (family), as for the REST-
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and HuggingFace-based entries.
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per model, this results in registry entries like `langchain.OpenAIChat.v1` - i.
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e. there is one registry entry per API and not per model (family), as for the
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REST- and HuggingFace-based entries. LangChain provides access to many more
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model that `spacy-llm` does natively, so if your model or provider of choice
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isn't available directly, just leverage the `langchain` integration by
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specifying your model with `langchain.YourModel.v1`!
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The name of the model to be used has to be passed in via the `name` attribute.
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@ -1560,7 +1564,7 @@ The name of the model to be used has to be passed in via the `name` attribute.
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>
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> ```ini
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> [components.llm.model]
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> @llm_models = "langchain.OpenAI.v1"
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> @llm_models = "langchain.OpenAIChat.v1"
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> name = "gpt-3.5-turbo"
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> query = {"@llm_queries": "spacy.CallLangChain.v1"}
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> config = {"temperature": 0.0}
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@ -107,7 +107,8 @@ factory = "llm"
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labels = ["COMPLIMENT", "INSULT"]
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[components.llm.model]
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@llm_models = "spacy.GPT-3-5.v1"
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@llm_models = "spacy.OpenAI.v1"
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name = "gpt-3.5-turbo"
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config = {"temperature": 0.0}
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```
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@ -146,7 +147,7 @@ factory = "llm"
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labels = ["PERSON", "ORGANISATION", "LOCATION"]
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[components.llm.model]
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@llm_models = "spacy.Dolly.v1"
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@llm_models = "spacy.HuggingFace.v1"
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# For better performance, use dolly-v2-12b instead
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name = "dolly-v2-3b"
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```
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@ -457,12 +458,13 @@ models by specifying one of the models registered with the `langchain.` prefix.
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_Why LangChain if there are also are native REST and HuggingFace interfaces? When should I use what?_
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Third-party libraries like `langchain` focus on prompt management, integration
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of many different LLM APIs, and other related features such as conversational
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memory or agents. `spacy-llm` on the other hand emphasizes features we consider
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useful in the context of NLP pipelines utilizing LLMs to process documents
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(mostly) independent from each other. It makes sense that the feature sets of
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such third-party libraries and `spacy-llm` aren't identical - and users might
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want to take advantage of features not available in `spacy-llm`.
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of many different LLM APIs and models, and other related features such as
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conversational memory or agents. `spacy-llm` on the other hand emphasizes
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features we consider useful in the context of NLP pipelines utilizing LLMs for
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(1) extractive NLP and (2) to process documents independent from each other. It
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makes sense that the feature sets of such third-party libraries and `spacy-llm`
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aren't identical - and users might want to take advantage of features not
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available in `spacy-llm`.
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The advantage of implementing our own REST and HuggingFace integrations is that
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we can ensure a larger degree of stability and robustness, as we can guarantee
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@ -481,36 +483,15 @@ provider's documentation.
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</Infobox>
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| Model | Description |
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| ----------------------------------------------------------------------- | ---------------------------------------------- |
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| [`spacy.GPT-4.v2`](/api/large-language-models#models-rest) | OpenAI’s `gpt-4` model family. |
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| [`spacy.GPT-3-5.v2`](/api/large-language-models#models-rest) | OpenAI’s `gpt-3-5` model family. |
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| [`spacy.Text-Davinci.v2`](/api/large-language-models#models-rest) | OpenAI’s `text-davinci` model family. |
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| [`spacy.Code-Davinci.v2`](/api/large-language-models#models-rest) | OpenAI’s `code-davinci` model family. |
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| [`spacy.Text-Curie.v2`](/api/large-language-models#models-rest) | OpenAI’s `text-curie` model family. |
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| [`spacy.Text-Babbage.v2`](/api/large-language-models#models-rest) | OpenAI’s `text-babbage` model family. |
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| [`spacy.Text-Ada.v2`](/api/large-language-models#models-rest) | OpenAI’s `text-ada` model family. |
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| [`spacy.Davinci.v2`](/api/large-language-models#models-rest) | OpenAI’s `davinci` model family. |
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| [`spacy.Curie.v2`](/api/large-language-models#models-rest) | OpenAI’s `curie` model family. |
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| [`spacy.Babbage.v2`](/api/large-language-models#models-rest) | OpenAI’s `babbage` model family. |
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| [`spacy.Ada.v2`](/api/large-language-models#models-rest) | OpenAI’s `ada` model family. |
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| [`spacy.Azure.v1`](/api/large-language-models#models-rest) | Azure's OpenAI models. |
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| [`spacy.Command.v1`](/api/large-language-models#models-rest) | Cohere’s `command` model family. |
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| [`spacy.Claude-2.v1`](/api/large-language-models#models-rest) | Anthropic’s `claude-2` model family. |
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| [`spacy.Claude-1.v1`](/api/large-language-models#models-rest) | Anthropic’s `claude-1` model family. |
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| [`spacy.Claude-instant-1.v1`](/api/large-language-models#models-rest) | Anthropic’s `claude-instant-1` model family. |
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| [`spacy.Claude-instant-1-1.v1`](/api/large-language-models#models-rest) | Anthropic’s `claude-instant-1.1` model family. |
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| [`spacy.Claude-1-0.v1`](/api/large-language-models#models-rest) | Anthropic’s `claude-1.0` model family. |
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| [`spacy.Claude-1-2.v1`](/api/large-language-models#models-rest) | Anthropic’s `claude-1.2` model family. |
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| [`spacy.Claude-1-3.v1`](/api/large-language-models#models-rest) | Anthropic’s `claude-1.3` model family. |
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| [`spacy.PaLM.v1`](/api/large-language-models#models-rest) | Google’s `PaLM` model family. |
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| [`spacy.Dolly.v1`](/api/large-language-models#models-hf) | Dolly models through HuggingFace. |
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| [`spacy.Falcon.v1`](/api/large-language-models#models-hf) | Falcon models through HuggingFace. |
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| [`spacy.Mistral.v1`](/api/large-language-models#models-hf) | Mistral models through HuggingFace. |
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| [`spacy.Llama2.v1`](/api/large-language-models#models-hf) | Llama2 models through HuggingFace. |
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| [`spacy.StableLM.v1`](/api/large-language-models#models-hf) | StableLM models through HuggingFace. |
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| [`spacy.OpenLLaMA.v1`](/api/large-language-models#models-hf) | OpenLLaMA models through HuggingFace. |
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| [LangChain models](/api/large-language-models#langchain-models) | LangChain models for API retrieval. |
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| Model | Description |
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| --------------------------------------------------------------- | -------------------------------------------------- |
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| [`spacy.OpenAI.v1`](/api/large-language-models#models-rest) | OpenAI's chat and completion models. |
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| [`spacy.Azure.v1`](/api/large-language-models#models-rest) | Azure's OpenAI models. |
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| [`spacy.Cohere.v1`](/api/large-language-models#models-rest) | Cohere’s text models. |
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| [`spacy.Anthropic.v1`](/api/large-language-models#models-rest) | Anthropic’s text models. |
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| [`spacy.Google.v1`](/api/large-language-models#models-rest) | Google’s text models (e. g. PaLM). |
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| [`spacy.HuggingFace.v1`](/api/large-language-models#models-hf) | A selection of LLMs available through HuggingFace. |
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| [LangChain models](/api/large-language-models#langchain-models) | All models available through `langchain`. |
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Note that the chat models variants of Llama 2 are currently not supported. This
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is because they need a particular prompting setup and don't add any discernible
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