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Clarify HuggingFace token handling in workspace, noting the standard CLI location and adding support for an environment variable.

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This commit is contained in:
Foke Singh 2023-03-14 15:28:03 +00:00
parent cd2f2209d0
commit fe531aef06
3 changed files with 21 additions and 16 deletions
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10
docs/howtos/huggingface_access_token.md
View File

@ -20,19 +20,19 @@ download models.
* store the token on your machine (replace the placeholder with your actual
token):
You can use the `HUGGINGFACE_TOKEN` environment variable to store the token or use
its standard location:
```
echo -n <hf_my_token> > `$HOME/.cache/huggingface/token`
mkdir -p $HOME/.cache/huggingface/; echo <hf_my_token> > "$HOME/.cache/huggingface/token"
```
The `-n` is important in order to not append an "end of line" character at the
end of the file that would corrupt the token.
Now you're ready to download a gated model like `Meta-Llama-3-8b`!
**Example:**
```
# requires token in $HOME/.cache/huggingface/token
# requires token in $HOME/.cache/huggingface/token, as created by the
# `huggingface-cli login` command, or the `HUGGINGFACE_TOKEN` environment variable.
cd examples
bazel run -c opt //llama:Meta-Llama-3-8b
bazel run -c opt //llama:Meta-Llama-3-8b -- --promt="Once upon a time,"

14
docs/huggingface-access-token.md
View File

@ -3,7 +3,10 @@
Some models have restrictions and may require some sort of approval or agreement
process, which, by consequence, **requires token-authentication with Huggingface**.
Here is how you can generate a **"read-only public repositories"** access token to log into your account on Huggingface, directly from `bazel`, in order to download models.
The easiest way might be to use the `huggingface-cli login` command.
Alternatively, here is how you can generate a **"read-only public repositories"**
access token to log into your account on Huggingface, directly from `bazel`, in order to download models.
* log in at [https://huggingface.co/settings/tokens](https://huggingface.co/settings/tokens).
* click on "Create new token"
@ -14,18 +17,19 @@ Here is how you can generate a **"read-only public repositories"** access token
* the token looks something like `hf_abCdEfGhijKlM`.
* store the token on your machine (replace the placeholder with your actual token):
You can use the `HUGGINGFACE_TOKEN` environment variable to store the token or use
its standard location:
```
mkdir -p $HOME/.cache/huggingface/; echo -n <hf_my_token> > "$HOME/.cache/huggingface/token"
mkdir -p $HOME/.cache/huggingface/; echo <hf_my_token> > "$HOME/.cache/huggingface/token"
```
The `-n` is important in order to not append an "end of line" character at the end of the file that would corrupt the token.
Now you're ready to download a gated model like `Meta-Llama-3-8b`!
**Example:**
```
# requires token in $HOME/.cache/huggingface/token
# requires token in $HOME/.cache/huggingface/token, as created by the
# `huggingface-cli login` command, or the `HUGGINGFACE_TOKEN` environment variable.
cd examples
bazel run -c opt //llama:Meta-Llama-3-8b
bazel run -c opt //llama:Meta-Llama-3-8b -- --promt="Once upon a time,"

13
docs/tutorials/getting_started.md
View File

@ -63,7 +63,7 @@ referred to as the "prompt".
To start, you can use a small model trained specifically on children's history
books. This model has been trained by [Andrej Karpathy](https://x.com/karpathy);
you can read more about it on his
you can read more about it on his
[Github](https://github.com/karpathy/llama2.c).
```
@ -86,14 +86,15 @@ This model has restrictions, see
[here](https://huggingface.co/meta-llama/Meta-Llama-3-8B): it **requires
approval from Meta on Huggingface**, which can take a few hours to get granted.
While waiting for approval, you can already
While waiting for approval, you can already
[generate your Huggingface access token](../howtos/huggingface_access_token.md).
Once you've been granted access, you're ready to download a gated model like
`Meta-Llama-3-8b`!
```
# requires token in $HOME/.cache/huggingface/token
# requires token in $HOME/.cache/huggingface/token, as created by the
# `huggingface-cli login` command, or the `HUGGINGFACE_TOKEN` environment variable.
cd examples
bazel run -c opt //llama:Meta-Llama-3-8b
bazel run -c opt //llama:Meta-Llama-3-8b -- --promt="Once upon a time,"
@ -134,12 +135,12 @@ bazel run -c opt //llama:OpenLLaMA-3B \
In [Deploying Models on a Server](../howtos/deploy_on_server.md), we show how you can
cross-compile and package for a specific architecture, then deploy and run your
model. Alternatively, you can also [dockerize](../howtos/dockerize_models.md) your
model. Alternatively, you can also [dockerize](../howtos/dockerize_models.md) your
model.
You might also want to check out the
[examples](https://github.com/zml/zml/tree/master/examples), read through the
[documentation](../README.md), start
[writing your first model](../tutorials/write_first_model.md), or read about more
[documentation](../README.md), start
[writing your first model](../tutorials/write_first_model.md), or read about more
high-level [ZML concepts](../learn/concepts.md).