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mradermacher
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Faro-Yi-34B-DPO-i1-GGUF

Transformers
GGUF
4 datasets
English
Chinese
Inference Endpoints
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@@ -7,6 +7,7 @@ datasets:
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  - jondurbin/truthy-dpo-v0.1
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  language:
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  - en
 
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  library_name: transformers
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  license: mit
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  quantized_by: mradermacher
@@ -34,7 +35,7 @@ more details, including on how to concatenate multi-part files.
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  | Link | Type | Size/GB | Notes |
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  |:-----|:-----|--------:|:------|
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  | [GGUF](https://huggingface.co/mradermacher/Faro-Yi-34B-DPO-i1-GGUF/resolve/main/Faro-Yi-34B-DPO.i1-IQ1_S.gguf) | i1-IQ1_S | 7.6 | for the desperate |
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- | [GGUF](https://huggingface.co/mradermacher/Faro-Yi-34B-DPO-i1-GGUF/resolve/main/Faro-Yi-34B-DPO.i1-IQ1_M.gguf) | i1-IQ1_M | 8.3 | for the desperate |
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  | [GGUF](https://huggingface.co/mradermacher/Faro-Yi-34B-DPO-i1-GGUF/resolve/main/Faro-Yi-34B-DPO.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 9.4 | |
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  | [GGUF](https://huggingface.co/mradermacher/Faro-Yi-34B-DPO-i1-GGUF/resolve/main/Faro-Yi-34B-DPO.i1-IQ2_XS.gguf) | i1-IQ2_XS | 10.4 | |
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  | [GGUF](https://huggingface.co/mradermacher/Faro-Yi-34B-DPO-i1-GGUF/resolve/main/Faro-Yi-34B-DPO.i1-IQ2_S.gguf) | i1-IQ2_S | 11.0 | |
@@ -55,7 +56,6 @@ more details, including on how to concatenate multi-part files.
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  | [GGUF](https://huggingface.co/mradermacher/Faro-Yi-34B-DPO-i1-GGUF/resolve/main/Faro-Yi-34B-DPO.i1-Q5_K_M.gguf) | i1-Q5_K_M | 24.4 | |
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  | [GGUF](https://huggingface.co/mradermacher/Faro-Yi-34B-DPO-i1-GGUF/resolve/main/Faro-Yi-34B-DPO.i1-Q6_K.gguf) | i1-Q6_K | 28.3 | practically like static Q6_K |
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-
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  Here is a handy graph by ikawrakow comparing some lower-quality quant
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  types (lower is better):
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  - jondurbin/truthy-dpo-v0.1
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  language:
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  - en
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+ - zh
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  library_name: transformers
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  license: mit
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  quantized_by: mradermacher
 
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  | Link | Type | Size/GB | Notes |
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  |:-----|:-----|--------:|:------|
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  | [GGUF](https://huggingface.co/mradermacher/Faro-Yi-34B-DPO-i1-GGUF/resolve/main/Faro-Yi-34B-DPO.i1-IQ1_S.gguf) | i1-IQ1_S | 7.6 | for the desperate |
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+ | [GGUF](https://huggingface.co/mradermacher/Faro-Yi-34B-DPO-i1-GGUF/resolve/main/Faro-Yi-34B-DPO.i1-IQ1_M.gguf) | i1-IQ1_M | 8.3 | mostly desperate |
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  | [GGUF](https://huggingface.co/mradermacher/Faro-Yi-34B-DPO-i1-GGUF/resolve/main/Faro-Yi-34B-DPO.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 9.4 | |
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  | [GGUF](https://huggingface.co/mradermacher/Faro-Yi-34B-DPO-i1-GGUF/resolve/main/Faro-Yi-34B-DPO.i1-IQ2_XS.gguf) | i1-IQ2_XS | 10.4 | |
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  | [GGUF](https://huggingface.co/mradermacher/Faro-Yi-34B-DPO-i1-GGUF/resolve/main/Faro-Yi-34B-DPO.i1-IQ2_S.gguf) | i1-IQ2_S | 11.0 | |
 
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  | [GGUF](https://huggingface.co/mradermacher/Faro-Yi-34B-DPO-i1-GGUF/resolve/main/Faro-Yi-34B-DPO.i1-Q5_K_M.gguf) | i1-Q5_K_M | 24.4 | |
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  | [GGUF](https://huggingface.co/mradermacher/Faro-Yi-34B-DPO-i1-GGUF/resolve/main/Faro-Yi-34B-DPO.i1-Q6_K.gguf) | i1-Q6_K | 28.3 | practically like static Q6_K |
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  Here is a handy graph by ikawrakow comparing some lower-quality quant
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  types (lower is better):
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