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Update docs w.r.t. PaLM support.

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Raphael Mitsch 2023-09-26 11:28:35 +02:00
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11
website/docs/api/large-language-models.mdx
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@ -19,8 +19,8 @@ prototyping** and **prompting**, and turning unstructured responses into
An LLM component is implemented through the `LLMWrapper` class. It is accessible
through a generic `llm`
[component factory](https://spacy.io/usage/processing-pipelines#custom-components-factories)
as well as through task-specific component factories: `llm_ner`, `llm_spancat`, `llm_rel`,
`llm_textcat`, `llm_sentiment` and `llm_summarization`.
as well as through task-specific component factories: `llm_ner`, `llm_spancat`,
`llm_rel`, `llm_textcat`, `llm_sentiment` and `llm_summarization`.
### LLMWrapper.\_\_init\_\_ {id="init",tag="method"}
@ -984,6 +984,7 @@ Currently, these models are provided as part of the core library:
| `spacy.Claude-1-3.v1` | Anthropic | `["claude-1.3", "claude-1.3-100k"]` | `"claude-1.3"` | `{}` |
| `spacy.Claude-instant-1.v1` | Anthropic | `["claude-instant-1", "claude-instant-1-100k"]` | `"claude-instant-1"` | `{}` |
| `spacy.Claude-instant-1-1.v1` | Anthropic | `["claude-instant-1.1", "claude-instant-1.1-100k"]` | `"claude-instant-1.1"` | `{}` |
| `spacy.PaLM.v1` | Google | `["chat-bison-001", "text-bison-001"]` | `"text-bison-001"` | `{temperature=0.0}` |
To use these models, make sure that you've [set the relevant API](#api-keys)
keys as environment variables.
@ -1014,6 +1015,12 @@ For Anthropic:
export ANTHROPIC_API_KEY="..."
```
For PaLM:
```shell
export PALM_API_KEY="..."
```
### Models via HuggingFace {id="models-hf"}
These models all take the same parameters:

5
website/docs/usage/large-language-models.mdx
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@ -170,8 +170,8 @@ to be `"databricks/dolly-v2-12b"` for better performance.
### Example 3: Create the component directly in Python {id="example-3"}
The `llm` component behaves as any other component does, and there are
[task-specific components](/api/large-language-models#config) defined to
help you hit the ground running with a reasonable built-in task implementation.
[task-specific components](/api/large-language-models#config) defined to help
you hit the ground running with a reasonable built-in task implementation.
```python
import spacy
@ -484,6 +484,7 @@ provider's documentation.
| [`spacy.Claude-1-0.v1`](/api/large-language-models#models-rest) | Anthropic’s `claude-1.0` model family. |
| [`spacy.Claude-1-2.v1`](/api/large-language-models#models-rest) | Anthropic’s `claude-1.2` model family. |
| [`spacy.Claude-1-3.v1`](/api/large-language-models#models-rest) | Anthropic’s `claude-1.3` model family. |
| [`spacy.PaLM.v1`](/api/large-language-models#models-rest) | Google’s `PaLM` model family. |
| [`spacy.Dolly.v1`](/api/large-language-models#models-hf) | Dolly models through HuggingFace. |
| [`spacy.Falcon.v1`](/api/large-language-models#models-hf) | Falcon models through HuggingFace. |
| [`spacy.Llama2.v1`](/api/large-language-models#models-hf) | Llama2 models through HuggingFace. |