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Yang An
2023-08-05 23:58:38 +08:00
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@@ -186,7 +186,7 @@ print(f'Response: {response}')
## Quantization ## Quantization
We provide examples to show how to load models in `NF4` and `Int8`. For starters, make sure you have implemented `bitsandbytes`. Note that the requirements for `bitsandbytes` is: We provide examples to show how to load models in `NF4` and `Int8`. For starters, make sure you have implemented `bitsandbytes`. Note that the requirements for `bitsandbytes` are:
``` ```
**Requirements** Python >=3.8. Linux distribution (Ubuntu, MacOS, etc.) + CUDA > 10.0. **Requirements** Python >=3.8. Linux distribution (Ubuntu, MacOS, etc.) + CUDA > 10.0.
@@ -197,7 +197,7 @@ Windows users should find another option, which might be [bitsandbytes-windows-w
Then you only need to add your quantization configuration to `AutoModelForCausalLM.from_pretrained`. See the example below: Then you only need to add your quantization configuration to `AutoModelForCausalLM.from_pretrained`. See the example below:
```python ```python
from transformers import BitsAndBytesConfig from transformers import AutoModelForCausalLM, BitsAndBytesConfig
# quantization configuration for NF4 (4 bits) # quantization configuration for NF4 (4 bits)
quantization_config = BitsAndBytesConfig( quantization_config = BitsAndBytesConfig(