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PrathameshLLM-7B-GGUF

Transformers
GGUF
text-generation-inference
unsloth
gemma
trl
Inference Endpoints
Model card Files Community
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  1. README.md +15 -2
README.md CHANGED
@@ -2,6 +2,20 @@
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  base_model: pmking27/PrathameshLLM-7B
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  language:
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  - en
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  library_name: transformers
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  license: apache-2.0
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  quantized_by: mradermacher
@@ -40,14 +54,13 @@ more details, including on how to concatenate multi-part files.
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  | [GGUF](https://huggingface.co/mradermacher/PrathameshLLM-7B-GGUF/resolve/main/PrathameshLLM-7B.IQ4_XS.gguf) | IQ4_XS | 1.6 | |
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  | [GGUF](https://huggingface.co/mradermacher/PrathameshLLM-7B-GGUF/resolve/main/PrathameshLLM-7B.Q4_0.gguf) | Q4_0 | 1.7 | fast, low quality |
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  | [GGUF](https://huggingface.co/mradermacher/PrathameshLLM-7B-GGUF/resolve/main/PrathameshLLM-7B.Q4_K_S.gguf) | Q4_K_S | 1.7 | fast, recommended |
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- | [GGUF](https://huggingface.co/mradermacher/PrathameshLLM-7B-GGUF/resolve/main/PrathameshLLM-7B.IQ4_NL.gguf) | IQ4_NL | 1.7 | slightly worse than Q4_K_S |
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  | [GGUF](https://huggingface.co/mradermacher/PrathameshLLM-7B-GGUF/resolve/main/PrathameshLLM-7B.Q4_K_M.gguf) | Q4_K_M | 1.7 | fast, recommended |
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  | [GGUF](https://huggingface.co/mradermacher/PrathameshLLM-7B-GGUF/resolve/main/PrathameshLLM-7B.Q5_K_S.gguf) | Q5_K_S | 1.9 | |
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  | [GGUF](https://huggingface.co/mradermacher/PrathameshLLM-7B-GGUF/resolve/main/PrathameshLLM-7B.Q5_K_M.gguf) | Q5_K_M | 1.9 | |
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  | [GGUF](https://huggingface.co/mradermacher/PrathameshLLM-7B-GGUF/resolve/main/PrathameshLLM-7B.Q6_K.gguf) | Q6_K | 2.2 | very good quality |
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  | [GGUF](https://huggingface.co/mradermacher/PrathameshLLM-7B-GGUF/resolve/main/PrathameshLLM-7B.Q8_0.gguf) | Q8_0 | 2.8 | fast, best quality |
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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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  base_model: pmking27/PrathameshLLM-7B
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  language:
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  - en
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+ - mr
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+ - hi
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+ - gu
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+ - pa
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+ - te
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+ - ta
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+ - ml
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+ - kn
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+ - sd
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+ - ne
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+ - ur
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+ - as
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+ - bn
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+ - or
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  library_name: transformers
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  license: apache-2.0
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  quantized_by: mradermacher
 
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  | [GGUF](https://huggingface.co/mradermacher/PrathameshLLM-7B-GGUF/resolve/main/PrathameshLLM-7B.IQ4_XS.gguf) | IQ4_XS | 1.6 | |
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  | [GGUF](https://huggingface.co/mradermacher/PrathameshLLM-7B-GGUF/resolve/main/PrathameshLLM-7B.Q4_0.gguf) | Q4_0 | 1.7 | fast, low quality |
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  | [GGUF](https://huggingface.co/mradermacher/PrathameshLLM-7B-GGUF/resolve/main/PrathameshLLM-7B.Q4_K_S.gguf) | Q4_K_S | 1.7 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/PrathameshLLM-7B-GGUF/resolve/main/PrathameshLLM-7B.IQ4_NL.gguf) | IQ4_NL | 1.7 | prefer IQ4_XS |
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  | [GGUF](https://huggingface.co/mradermacher/PrathameshLLM-7B-GGUF/resolve/main/PrathameshLLM-7B.Q4_K_M.gguf) | Q4_K_M | 1.7 | fast, recommended |
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  | [GGUF](https://huggingface.co/mradermacher/PrathameshLLM-7B-GGUF/resolve/main/PrathameshLLM-7B.Q5_K_S.gguf) | Q5_K_S | 1.9 | |
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  | [GGUF](https://huggingface.co/mradermacher/PrathameshLLM-7B-GGUF/resolve/main/PrathameshLLM-7B.Q5_K_M.gguf) | Q5_K_M | 1.9 | |
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  | [GGUF](https://huggingface.co/mradermacher/PrathameshLLM-7B-GGUF/resolve/main/PrathameshLLM-7B.Q6_K.gguf) | Q6_K | 2.2 | very good quality |
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  | [GGUF](https://huggingface.co/mradermacher/PrathameshLLM-7B-GGUF/resolve/main/PrathameshLLM-7B.Q8_0.gguf) | Q8_0 | 2.8 | fast, best quality |
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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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