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@@ -23,7 +23,6 @@ CodeFuse-CodeLlama-34B-4bits is the 4-bit quantized version of CodeFuse-CodeLlam
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  After undergoing 4-bit quantization, the CodeFuse-CodeLlama-34B-4bits model can be loaded on either a single A10 (24GB VRAM) or a RTX 4090 (24GB VRAM). Moreover, the quantized model still achives an impressive accuracy of 73.8% on the Humaneval pass@1 metric.
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  <br>
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  ## News and Updates
@@ -205,8 +204,6 @@ Here, SHA256 values are provided for the model-related files for consistency che
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  |tokenizer.model | 9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347 |
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  |tokenizer_config.json | c12441e82f2dce0baff87cf5948e82d6e9b51cc0b5266369c30c319fb771eeb2 |
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  <br>
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  ## Citation
@@ -221,6 +218,7 @@ If you find our [work](https://arxiv.org/abs/2311.02303) useful or helpful for y
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  eprint={2311.02303}
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  }
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  ```
 
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  <a id="chinese"></a>
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  After undergoing 4-bit quantization, the CodeFuse-CodeLlama-34B-4bits model can be loaded on either a single A10 (24GB VRAM) or a RTX 4090 (24GB VRAM). Moreover, the quantized model still achives an impressive accuracy of 73.8% on the Humaneval pass@1 metric.
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  <br>
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  ## News and Updates
 
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  |tokenizer.model | 9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347 |
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  |tokenizer_config.json | c12441e82f2dce0baff87cf5948e82d6e9b51cc0b5266369c30c319fb771eeb2 |
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  <br>
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  ## Citation
 
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  eprint={2311.02303}
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  }
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  ```
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+ <br>
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  <a id="chinese"></a>
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