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metadata
license: other
base_model: cognitivecomputations/dolphin-2.9.1-llama-3-8b
tags:
  - generated_from_trainer
  - axolotl
  - TensorBlock
  - GGUF
datasets:
  - cognitivecomputations/Dolphin-2.9
  - teknium/OpenHermes-2.5
  - m-a-p/CodeFeedback-Filtered-Instruction
  - cognitivecomputations/dolphin-coder
  - cognitivecomputations/samantha-data
  - microsoft/orca-math-word-problems-200k
  - Locutusque/function-calling-chatml
  - internlm/Agent-FLAN
model-index:
  - name: out
    results: []
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cognitivecomputations/dolphin-2.9.1-llama-3-8b - GGUF

This repo contains GGUF format model files for cognitivecomputations/dolphin-2.9.1-llama-3-8b.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

Prompt template

<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Model file specification

Filename Quant type File Size Description
dolphin-2.9.1-llama-3-8b-Q2_K.gguf Q2_K 2.961 GB smallest, significant quality loss - not recommended for most purposes
dolphin-2.9.1-llama-3-8b-Q3_K_S.gguf Q3_K_S 3.413 GB very small, high quality loss
dolphin-2.9.1-llama-3-8b-Q3_K_M.gguf Q3_K_M 3.743 GB very small, high quality loss
dolphin-2.9.1-llama-3-8b-Q3_K_L.gguf Q3_K_L 4.025 GB small, substantial quality loss
dolphin-2.9.1-llama-3-8b-Q4_0.gguf Q4_0 4.341 GB legacy; small, very high quality loss - prefer using Q3_K_M
dolphin-2.9.1-llama-3-8b-Q4_K_S.gguf Q4_K_S 4.370 GB small, greater quality loss
dolphin-2.9.1-llama-3-8b-Q4_K_M.gguf Q4_K_M 4.583 GB medium, balanced quality - recommended
dolphin-2.9.1-llama-3-8b-Q5_0.gguf Q5_0 5.215 GB legacy; medium, balanced quality - prefer using Q4_K_M
dolphin-2.9.1-llama-3-8b-Q5_K_S.gguf Q5_K_S 5.215 GB large, low quality loss - recommended
dolphin-2.9.1-llama-3-8b-Q5_K_M.gguf Q5_K_M 5.339 GB large, very low quality loss - recommended
dolphin-2.9.1-llama-3-8b-Q6_K.gguf Q6_K 6.143 GB very large, extremely low quality loss
dolphin-2.9.1-llama-3-8b-Q8_0.gguf Q8_0 7.954 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/dolphin-2.9.1-llama-3-8b-GGUF --include "dolphin-2.9.1-llama-3-8b-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/dolphin-2.9.1-llama-3-8b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'