Initial GPTQ model commit

README.md

@@ -82,14 +82,14 @@ All GPTQ files are made with AutoGPTQ.
 
 | Branch | Bits | GS | Act Order | Damp % | GPTQ Dataset | Seq Len | Size | ExLlama | Desc |
 | ------ | ---- | -- | --------- | ------ | ------------ | ------- | ---- | ------- | ---- |
-| [main](https://huggingface.co/TheBloke/Vigogne-2-7B-Chat-GPTQ/tree/main) | 4 | 128 | No | 0.1 | french | 4096 | 3.90 GB | Yes | Most compatible option. Good inference speed in AutoGPTQ and GPTQ-for-LLaMa. Lower inference quality than other options. | 
-| [gptq-4bit-32g-actorder_True](https://huggingface.co/TheBloke/Vigogne-2-7B-Chat-GPTQ/tree/gptq-4bit-32g-actorder_True) | 4 | 32 | Yes | 0.1 | french | 4096 | 4.28 GB | Yes | 4-bit, with Act Order and group size 32g. Gives highest possible inference quality, with maximum VRAM usage. Poor AutoGPTQ CUDA speed. | 
-| [gptq-4bit-64g-actorder_True](https://huggingface.co/TheBloke/Vigogne-2-7B-Chat-GPTQ/tree/gptq-4bit-64g-actorder_True) | 4 | 64 | Yes | 0.1 | french | 4096 | 4.02 GB | Yes | 4-bit, with Act Order and group size 64g. Uses less VRAM than 32g, but with slightly lower accuracy. Poor AutoGPTQ CUDA speed. | 
-| [gptq-4bit-128g-actorder_True](https://huggingface.co/TheBloke/Vigogne-2-7B-Chat-GPTQ/tree/gptq-4bit-128g-actorder_True) | 4 | 128 | Yes | 0.1 | french | 4096 | 3.90 GB | Yes | 4-bit, with Act Order and group size 128g. Uses even less VRAM than 64g, but with slightly lower accuracy. Poor AutoGPTQ CUDA speed. | 
-| [gptq-8bit--1g-actorder_True](https://huggingface.co/TheBloke/Vigogne-2-7B-Chat-GPTQ/tree/gptq-8bit--1g-actorder_True) | 8 | None | Yes | 0.1 | french | 4096 | 7.01 GB | No | 8-bit, with Act Order. No group size, to lower VRAM requirements and to improve AutoGPTQ speed. | 
-| [gptq-8bit-128g-actorder_False](https://huggingface.co/TheBloke/Vigogne-2-7B-Chat-GPTQ/tree/gptq-8bit-128g-actorder_False) | 8 | 128 | No | 0.1 | french | 4096 | 7.16 GB | No | 8-bit, with group size 128g for higher inference quality and without Act Order to improve AutoGPTQ speed. | 
-| [gptq-8bit-128g-actorder_True](https://huggingface.co/TheBloke/Vigogne-2-7B-Chat-GPTQ/tree/gptq-8bit-128g-actorder_True) | 8 | 128 | Yes | 0.1 | french | 4096 | 7.16 GB | No | 8-bit, with group size 128g for higher inference quality and with Act Order for even higher accuracy. Poor AutoGPTQ CUDA speed. | 
-| [gptq-8bit-64g-actorder_True](https://huggingface.co/TheBloke/Vigogne-2-7B-Chat-GPTQ/tree/gptq-8bit-64g-actorder_True) | 8 | 64 | Yes | 0.1 | french | 4096 | 7.31 GB | No | 8-bit, with group size 64g and Act Order for maximum inference quality. Poor AutoGPTQ CUDA speed. |
+| [main](https://huggingface.co/TheBloke/Vigogne-2-7B-Chat-GPTQ/tree/main) | 4 | 128 | No | 0.1 | [French news](https://huggingface.co/datasets/gustavecortal/diverse_french_news) | 4096 | 3.90 GB | Yes | Most compatible option. Good inference speed in AutoGPTQ and GPTQ-for-LLaMa. Lower inference quality than other options. | 
+| [gptq-4bit-32g-actorder_True](https://huggingface.co/TheBloke/Vigogne-2-7B-Chat-GPTQ/tree/gptq-4bit-32g-actorder_True) | 4 | 32 | Yes | 0.1 | [French news](https://huggingface.co/datasets/gustavecortal/diverse_french_news) | 4096 | 4.28 GB | Yes | 4-bit, with Act Order and group size 32g. Gives highest possible inference quality, with maximum VRAM usage. Poor AutoGPTQ CUDA speed. | 
+| [gptq-4bit-64g-actorder_True](https://huggingface.co/TheBloke/Vigogne-2-7B-Chat-GPTQ/tree/gptq-4bit-64g-actorder_True) | 4 | 64 | Yes | 0.1 | [French news](https://huggingface.co/datasets/gustavecortal/diverse_french_news) | 4096 | 4.02 GB | Yes | 4-bit, with Act Order and group size 64g. Uses less VRAM than 32g, but with slightly lower accuracy. Poor AutoGPTQ CUDA speed. | 
+| [gptq-4bit-128g-actorder_True](https://huggingface.co/TheBloke/Vigogne-2-7B-Chat-GPTQ/tree/gptq-4bit-128g-actorder_True) | 4 | 128 | Yes | 0.1 | [French news](https://huggingface.co/datasets/gustavecortal/diverse_french_news) | 4096 | 3.90 GB | Yes | 4-bit, with Act Order and group size 128g. Uses even less VRAM than 64g, but with slightly lower accuracy. Poor AutoGPTQ CUDA speed. | 
+| [gptq-8bit--1g-actorder_True](https://huggingface.co/TheBloke/Vigogne-2-7B-Chat-GPTQ/tree/gptq-8bit--1g-actorder_True) | 8 | None | Yes | 0.1 | [French news](https://huggingface.co/datasets/gustavecortal/diverse_french_news) | 4096 | 7.01 GB | No | 8-bit, with Act Order. No group size, to lower VRAM requirements and to improve AutoGPTQ speed. | 
+| [gptq-8bit-128g-actorder_False](https://huggingface.co/TheBloke/Vigogne-2-7B-Chat-GPTQ/tree/gptq-8bit-128g-actorder_False) | 8 | 128 | No | 0.1 | [French news](https://huggingface.co/datasets/gustavecortal/diverse_french_news) | 4096 | 7.16 GB | No | 8-bit, with group size 128g for higher inference quality and without Act Order to improve AutoGPTQ speed. | 
+| [gptq-8bit-128g-actorder_True](https://huggingface.co/TheBloke/Vigogne-2-7B-Chat-GPTQ/tree/gptq-8bit-128g-actorder_True) | 8 | 128 | Yes | 0.1 | [French news](https://huggingface.co/datasets/gustavecortal/diverse_french_news) | 4096 | 7.16 GB | No | 8-bit, with group size 128g for higher inference quality and with Act Order for even higher accuracy. Poor AutoGPTQ CUDA speed. | 
+| [gptq-8bit-64g-actorder_True](https://huggingface.co/TheBloke/Vigogne-2-7B-Chat-GPTQ/tree/gptq-8bit-64g-actorder_True) | 8 | 64 | Yes | 0.1 | [French news](https://huggingface.co/datasets/gustavecortal/diverse_french_news) | 4096 | 7.31 GB | No | 8-bit, with group size 64g and Act Order for maximum inference quality. Poor AutoGPTQ CUDA speed. |
 
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