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RichardErkhov/
Yhhhhhhhhh_-_final-DEC-deepseek-coder-1.3b-instruct-gguf

Name: Yhhhhhhhhh_-_final-DEC-deepseek-coder-1.3b-instruct-gguf
Availability: InStock

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Quantization made by Richard Erkhov.

final-DEC-deepseek-coder-1.3b-instruct - GGUF

Name	Quant method	Size
final-DEC-deepseek-coder-1.3b-instruct.Q2_K.gguf	Q2_K	0.52GB
final-DEC-deepseek-coder-1.3b-instruct.IQ3_XS.gguf	IQ3_XS	0.57GB
final-DEC-deepseek-coder-1.3b-instruct.IQ3_S.gguf	IQ3_S	0.6GB
final-DEC-deepseek-coder-1.3b-instruct.Q3_K_S.gguf	Q3_K_S	0.6GB
final-DEC-deepseek-coder-1.3b-instruct.IQ3_M.gguf	IQ3_M	0.63GB
final-DEC-deepseek-coder-1.3b-instruct.Q3_K.gguf	Q3_K	0.66GB
final-DEC-deepseek-coder-1.3b-instruct.Q3_K_M.gguf	Q3_K_M	0.66GB
final-DEC-deepseek-coder-1.3b-instruct.Q3_K_L.gguf	Q3_K_L	0.69GB
final-DEC-deepseek-coder-1.3b-instruct.IQ4_XS.gguf	IQ4_XS	0.7GB
final-DEC-deepseek-coder-1.3b-instruct.Q4_0.gguf	Q4_0	0.72GB
final-DEC-deepseek-coder-1.3b-instruct.IQ4_NL.gguf	IQ4_NL	0.73GB
final-DEC-deepseek-coder-1.3b-instruct.Q4_K_S.gguf	Q4_K_S	0.76GB
final-DEC-deepseek-coder-1.3b-instruct.Q4_K.gguf	Q4_K	0.81GB
final-DEC-deepseek-coder-1.3b-instruct.Q4_K_M.gguf	Q4_K_M	0.81GB
final-DEC-deepseek-coder-1.3b-instruct.Q4_1.gguf	Q4_1	0.8GB
final-DEC-deepseek-coder-1.3b-instruct.Q5_0.gguf	Q5_0	0.87GB
final-DEC-deepseek-coder-1.3b-instruct.Q5_K_S.gguf	Q5_K_S	0.89GB
final-DEC-deepseek-coder-1.3b-instruct.Q5_K.gguf	Q5_K	0.93GB
final-DEC-deepseek-coder-1.3b-instruct.Q5_K_M.gguf	Q5_K_M	0.93GB
final-DEC-deepseek-coder-1.3b-instruct.Q5_1.gguf	Q5_1	0.95GB
final-DEC-deepseek-coder-1.3b-instruct.Q6_K.gguf	Q6_K	1.09GB
final-DEC-deepseek-coder-1.3b-instruct.Q8_0.gguf	Q8_0	1.33GB

Original model description:

library_name: transformers license: other base_model: Yhhhhhhhhh/final-tc-deepseek-coder-1.3b-instruct tags:

This model is a fine-tuned version of /content/drive/MyDrive/Effi-Code/LLaMA-Factory/saves/nopy_tc_final_sft_deepseek-coder-1.3b-instruct on the output dataset. It achieves the following results on the evaluation set:

More information needed

More information needed

More information needed

The following hyperparameters were used during training: