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![]() * Add `model_config` parameter to `load()` and `load_model()`
For easy editing of the loaded model configuration (e.g., for changing RoPE theta or scaling of Phi-3 model)
Example:
```python
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Phi-3-mini-4k-instruct-4bit-no-q-embed", model_config={"rope_theta":50000.0})
response = generate(model, tokenizer, prompt, max_tokens=MAX_TOKENS)
```
* Possible bug (default_loss)
* Revert "Possible bug (default_loss)"
This reverts commit
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.. | ||
examples | ||
models | ||
tuner | ||
__init__.py | ||
convert.py | ||
fuse.py | ||
generate.py | ||
gguf.py | ||
LORA.md | ||
lora.py | ||
MANAGE.md | ||
manage.py | ||
MERGE.md | ||
merge.py | ||
py.typed | ||
README.md | ||
requirements.txt | ||
sample_utils.py | ||
SERVER.md | ||
server.py | ||
tokenizer_utils.py | ||
UPLOAD.md | ||
utils.py | ||
version.py |
Generate Text with MLX and 🤗 Hugging Face
This an example of large language model text generation that can pull models from the Hugging Face Hub.
For more information on this example, see the README in the parent directory.
This package also supports fine tuning with LoRA or QLoRA. For more information see the LoRA documentation.