Update README.md

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	---
	base_model: impactframes/QWQCoder
	library_name: transformers
	tags:
	- mergekit
	- merge
	- TensorBlock
	- GGUF
	---

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	## impactframes/QWQCoder - GGUF

	This repo contains GGUF format model files for [impactframes/QWQCoder](https://huggingface.co/impactframes/QWQCoder).

	The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).

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	## 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 \|
	\| -------- \| ---------- \| --------- \| ----------- \|
	\| [QWQCoder-Q2_K.gguf](https://huggingface.co/tensorblock/QWQCoder-GGUF/blob/main/QWQCoder-Q2_K.gguf) \| Q2_K \| 6.607 GB \| smallest, significant quality loss - not recommended for most purposes \|
	\| [QWQCoder-Q3_K_S.gguf](https://huggingface.co/tensorblock/QWQCoder-GGUF/blob/main/QWQCoder-Q3_K_S.gguf) \| Q3_K_S \| 7.686 GB \| very small, high quality loss \|
	\| [QWQCoder-Q3_K_M.gguf](https://huggingface.co/tensorblock/QWQCoder-GGUF/blob/main/QWQCoder-Q3_K_M.gguf) \| Q3_K_M \| 8.458 GB \| very small, high quality loss \|
	\| [QWQCoder-Q3_K_L.gguf](https://huggingface.co/tensorblock/QWQCoder-GGUF/blob/main/QWQCoder-Q3_K_L.gguf) \| Q3_K_L \| 9.113 GB \| small, substantial quality loss \|
	\| [QWQCoder-Q4_0.gguf](https://huggingface.co/tensorblock/QWQCoder-GGUF/blob/main/QWQCoder-Q4_0.gguf) \| Q4_0 \| 9.861 GB \| legacy; small, very high quality loss - prefer using Q3_K_M \|
	\| [QWQCoder-Q4_K_S.gguf](https://huggingface.co/tensorblock/QWQCoder-GGUF/blob/main/QWQCoder-Q4_K_S.gguf) \| Q4_K_S \| 9.935 GB \| small, greater quality loss \|
	\| [QWQCoder-Q4_K_M.gguf](https://huggingface.co/tensorblock/QWQCoder-GGUF/blob/main/QWQCoder-Q4_K_M.gguf) \| Q4_K_M \| 10.467 GB \| medium, balanced quality - recommended \|
	\| [QWQCoder-Q5_0.gguf](https://huggingface.co/tensorblock/QWQCoder-GGUF/blob/main/QWQCoder-Q5_0.gguf) \| Q5_0 \| 11.909 GB \| legacy; medium, balanced quality - prefer using Q4_K_M \|
	\| [QWQCoder-Q5_K_S.gguf](https://huggingface.co/tensorblock/QWQCoder-GGUF/blob/main/QWQCoder-Q5_K_S.gguf) \| Q5_K_S \| 11.909 GB \| large, low quality loss - recommended \|
	\| [QWQCoder-Q5_K_M.gguf](https://huggingface.co/tensorblock/QWQCoder-GGUF/blob/main/QWQCoder-Q5_K_M.gguf) \| Q5_K_M \| 12.221 GB \| large, very low quality loss - recommended \|
	\| [QWQCoder-Q6_K.gguf](https://huggingface.co/tensorblock/QWQCoder-GGUF/blob/main/QWQCoder-Q6_K.gguf) \| Q6_K \| 14.085 GB \| very large, extremely low quality loss \|
	\| [QWQCoder-Q8_0.gguf](https://huggingface.co/tensorblock/QWQCoder-GGUF/blob/main/QWQCoder-Q8_0.gguf) \| Q8_0 \| 18.241 GB \| very large, extremely low quality loss - not recommended \|


	## Downloading instruction

	### Command line

	Firstly, install Huggingface Client

	```shell
	pip install -U "huggingface_hub[cli]"
	```

	Then, downoad the individual model file the a local directory

	```shell
	huggingface-cli download tensorblock/QWQCoder-GGUF --include "QWQCoder-Q2_K.gguf" --local-dir MY_LOCAL_DIR
	```

	If you wanna download multiple model files with a pattern (e.g., `Q4_Kgguf`), you can try:

	```shell
	huggingface-cli download tensorblock/QWQCoder-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='Q4_Kgguf'
	```