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Add links to Hugging Face Hub docs (#518)

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This PR adds some tweaks to the Hugging Face docs, mostly with links to
the Hub + relevant docs.
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docs/ecosystem/huggingface.md
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@ -1,15 +1,16 @@
# Hugging Face
This page covers how to use the Hugging Face ecosystem (including the Hugging Face Hub) within LangChain.
This page covers how to use the Hugging Face ecosystem (including the [Hugging Face Hub](https://huggingface.co)) within LangChain.
It is broken into two parts: installation and setup, and then references to specific Hugging Face wrappers.
## Installation and Setup
If you want to work with the Hugging Face Hub:
- Install the Python SDK with `pip install huggingface_hub`
- Get an OpenAI api key and set it as an environment variable (`HUGGINGFACEHUB_API_TOKEN`)
- Install the Hub client library with `pip install huggingface_hub`
- Create a Hugging Face account (it's free!)
- Create an [access token](https://huggingface.co/docs/hub/security-tokens) and set it as an environment variable (`HUGGINGFACEHUB_API_TOKEN`)
If you want work with Hugging Face python libraries:
If you want work with the Hugging Face Python libraries:
- Install `pip install transformers` for working with models and tokenizers
- Install `pip install datasets` for working with datasets
@ -18,7 +19,7 @@ If you want work with Hugging Face python libraries:
### LLM
There exists two Hugging Face LLM wrappers, one for a local pipeline and one for a model hosted on Hugging Face Hub.
Note that these wrappers only work for the following tasks: `text2text-generation`, `text-generation`
Note that these wrappers only work for models that support the following tasks: [`text2text-generation`](https://huggingface.co/models?library=transformers&pipeline_tag=text2text-generation&sort=downloads), [`text-generation`](https://huggingface.co/models?library=transformers&pipeline_tag=text-classification&sort=downloads)
To use the local pipeline wrapper:
```python
@ -35,7 +36,7 @@ For a more detailed walkthrough of the Hugging Face Hub wrapper, see [this noteb
### Embeddings
There exists two Hugging Face Embeddings wrappers, one for a local model and one for a model hosted on Hugging Face Hub.
Note that these wrappers only work for `sentence-transformers` models.
Note that these wrappers only work for [`sentence-transformers` models](https://huggingface.co/models?library=sentence-transformers&sort=downloads).
To use the local pipeline wrapper:
```python
@ -63,6 +64,6 @@ For a more detailed walkthrough of this, see [this notebook](../modules/utils/co
### Datasets
Hugging Face has lots of great datasets that can be used to evaluate your LLM chains.
The Hugging Face Hub has lots of great [datasets](https://huggingface.co/datasets) that can be used to evaluate your LLM chains.
For a detailed walkthrough of how to use them to do so, see [this notebook](../use_cases/evaluation/huggingface_datasets.ipynb)