Text Generation
GGUF
English
gpt2
dpo
trl
TensorBlock
GGUF
Eval Results
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Sharathhebbar24/chat_gpt2_dpo - GGUF

This repo contains GGUF format model files for Sharathhebbar24/chat_gpt2_dpo.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

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## Prompt template

Model file specification

Filename Quant type File Size Description
chat_gpt2_dpo-Q2_K.gguf Q2_K 0.081 GB smallest, significant quality loss - not recommended for most purposes
chat_gpt2_dpo-Q3_K_S.gguf Q3_K_S 0.090 GB very small, high quality loss
chat_gpt2_dpo-Q3_K_M.gguf Q3_K_M 0.098 GB very small, high quality loss
chat_gpt2_dpo-Q3_K_L.gguf Q3_K_L 0.102 GB small, substantial quality loss
chat_gpt2_dpo-Q4_0.gguf Q4_0 0.107 GB legacy; small, very high quality loss - prefer using Q3_K_M
chat_gpt2_dpo-Q4_K_S.gguf Q4_K_S 0.107 GB small, greater quality loss
chat_gpt2_dpo-Q4_K_M.gguf Q4_K_M 0.113 GB medium, balanced quality - recommended
chat_gpt2_dpo-Q5_0.gguf Q5_0 0.122 GB legacy; medium, balanced quality - prefer using Q4_K_M
chat_gpt2_dpo-Q5_K_S.gguf Q5_K_S 0.122 GB large, low quality loss - recommended
chat_gpt2_dpo-Q5_K_M.gguf Q5_K_M 0.127 GB large, very low quality loss - recommended
chat_gpt2_dpo-Q6_K.gguf Q6_K 0.138 GB very large, extremely low quality loss
chat_gpt2_dpo-Q8_0.gguf Q8_0 0.178 GB very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/chat_gpt2_dpo-GGUF --include "chat_gpt2_dpo-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/chat_gpt2_dpo-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
383
GGUF
Model size
163M params
Architecture
gpt2
Hardware compatibility
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Datasets used to train tensorblock/chat_gpt2_dpo-GGUF

Evaluation results