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metadata
license: apache-2.0
language:
  - en
pipeline_tag: text-generation
tags:
  - chat
  - qwen
  - qwen2
  - finetune
  - chatml
  - OpenHermes-2.5
  - HelpSteer2
  - Orca
  - SlimOrca
  - TensorBlock
  - GGUF
library_name: transformers
inference: false
model_creator: MaziyarPanahi
quantized_by: MaziyarPanahi
base_model: MaziyarPanahi/calme-2.5-qwen2-7b
model_name: calme-2.5-qwen2-7b
datasets:
  - nvidia/HelpSteer2
  - teknium/OpenHermes-2.5
  - microsoft/orca-math-word-problems-200k
  - Open-Orca/SlimOrca
TensorBlock

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MaziyarPanahi/calme-2.5-qwen2-7b - GGUF

This repo contains GGUF format model files for MaziyarPanahi/calme-2.5-qwen2-7b.

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
calme-2.5-qwen2-7b-Q2_K.gguf Q2_K 2.809 GB smallest, significant quality loss - not recommended for most purposes
calme-2.5-qwen2-7b-Q3_K_S.gguf Q3_K_S 3.253 GB very small, high quality loss
calme-2.5-qwen2-7b-Q3_K_M.gguf Q3_K_M 3.547 GB very small, high quality loss
calme-2.5-qwen2-7b-Q3_K_L.gguf Q3_K_L 3.808 GB small, substantial quality loss
calme-2.5-qwen2-7b-Q4_0.gguf Q4_0 4.127 GB legacy; small, very high quality loss - prefer using Q3_K_M
calme-2.5-qwen2-7b-Q4_K_S.gguf Q4_K_S 4.152 GB small, greater quality loss
calme-2.5-qwen2-7b-Q4_K_M.gguf Q4_K_M 4.361 GB medium, balanced quality - recommended
calme-2.5-qwen2-7b-Q5_0.gguf Q5_0 4.950 GB legacy; medium, balanced quality - prefer using Q4_K_M
calme-2.5-qwen2-7b-Q5_K_S.gguf Q5_K_S 4.950 GB large, low quality loss - recommended
calme-2.5-qwen2-7b-Q5_K_M.gguf Q5_K_M 5.071 GB large, very low quality loss - recommended
calme-2.5-qwen2-7b-Q6_K.gguf Q6_K 5.825 GB very large, extremely low quality loss
calme-2.5-qwen2-7b-Q8_0.gguf Q8_0 7.542 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/calme-2.5-qwen2-7b-GGUF --include "calme-2.5-qwen2-7b-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/calme-2.5-qwen2-7b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'