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Fix bug in upload + docs nit (#981)

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* fix bug in upload + docs nit

* nit
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Awni Hannun 2024-09-07 14:46:57 -07:00 committed by GitHub
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2 changed files with 8 additions and 24 deletions
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30
llms/mlx_lm/LORA.md
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@ -166,44 +166,28 @@ Currently, `*.jsonl` files support three data formats: `chat`,
`chat`: `chat`:
```jsonl ```jsonl
{ {"messages": [{"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": "Hello."}, {"role": "assistant", "content": "How can I assistant you today."}]}
"messages": [
{
"role": "system",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": "Hello."
},
{
"role": "assistant",
"content": "How can I assistant you today."
}
]
}
``` ```
`completions`: `completions`:
```jsonl ```jsonl
{ {"prompt": "What is the capital of France?", "completion": "Paris."}
"prompt": "What is the capital of France?",
"completion": "Paris."
}
``` ```
`text`: `text`:
```jsonl ```jsonl
{ {"text": "This is an example for the model."}
"text": "This is an example for the model."
}
``` ```
Note, the format is automatically determined by the dataset. Note also, keys in Note, the format is automatically determined by the dataset. Note also, keys in
each line not expected by the loader will be ignored. each line not expected by the loader will be ignored.
> [!NOTE]
> Each example in the datasets must be on a single line. Do not put more than
> one example per line and do not split an example accross multiple lines.
### Hugging Face Datasets ### Hugging Face Datasets
To use Hugging Face datasets, first install the `datasets` package: To use Hugging Face datasets, first install the `datasets` package:

2
llms/mlx_lm/utils.py
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@ -581,7 +581,7 @@ def upload_to_hub(path: str, upload_repo: str, hf_path: str):
prompt="hello" prompt="hello"
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None: if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}] messages = [{{"role": "user", "content": prompt}}]
prompt = tokenizer.apply_chat_template( prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True messages, tokenize=False, add_generation_prompt=True
) )