Currently investigating issue quantizing imatirx variants.

For static quants, visit legraphista/Qwen2-57B-A14B-Instruct-GGUF

[  12/ 479]           blk.0.ffn_gate_exps.weight - [ 3584,  2560,    64,     1], type =    f32, converting to q4_K .. ggml_validate_row_data: found nan value at block 1
ggml_validate_row_data: found nan value at block 0
ggml_validate_row_data: found nan value at block 0
ggml_validate_row_data: found nan value at block 0
ggml_validate_row_data: found nan value at block 14
  

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Qwen2-57B-A14B-Instruct-IMat-GGUF

Llama.cpp imatrix quantization of Qwen/Qwen2-57B-A14B-Instruct

Original Model: Qwen/Qwen2-57B-A14B-Instruct
Original dtype: BF16 (bfloat16)
Quantized by: llama.cpp b3091
IMatrix dataset: here

• Files
  • IMatrix
  • Common Quants
  • All Quants
• Downloading using huggingface-cli
• Inference
  • Simple chat template
  • Chat template with system prompt
  • Llama.cpp
• FAQ
  • Why is the IMatrix not applied everywhere?
  • How do I merge a split GGUF?

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Files

IMatrix

Status: ✅ Available
Link: here

Common Quants

Filename	Quant type	File Size	Status	Uses IMatrix	Is Split
Qwen2-57B-A14B-Instruct.Q8_0/*	Q8_0	61.02GB	✅ Available	⚪ Static	✂ Yes
Qwen2-57B-A14B-Instruct.Q6_K/*	Q6_K	47.12GB	✅ Available	⚪ Static	✂ Yes
Qwen2-57B-A14B-Instruct.Q4_K	Q4_K	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.Q3_K	Q3_K	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.Q2_K	Q2_K	-	⏳ Processing	🟢 IMatrix	-

All Quants

Filename	Quant type	File Size	Status	Uses IMatrix	Is Split
Qwen2-57B-A14B-Instruct.BF16/*	BF16	114.84GB	✅ Available	⚪ Static	✂ Yes
Qwen2-57B-A14B-Instruct.FP16/*	F16	114.84GB	✅ Available	⚪ Static	✂ Yes
Qwen2-57B-A14B-Instruct.Q8_0/*	Q8_0	61.02GB	✅ Available	⚪ Static	✂ Yes
Qwen2-57B-A14B-Instruct.Q6_K/*	Q6_K	47.12GB	✅ Available	⚪ Static	✂ Yes
Qwen2-57B-A14B-Instruct.Q5_K.gguf	Q5_K	40.80GB	✅ Available	⚪ Static	📦 No
Qwen2-57B-A14B-Instruct.Q5_K_S.gguf	Q5_K_S	39.57GB	✅ Available	⚪ Static	📦 No
Qwen2-57B-A14B-Instruct.Q4_K	Q4_K	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.Q4_K_S	Q4_K_S	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.IQ4_NL	IQ4_NL	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.IQ4_XS	IQ4_XS	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.Q3_K	Q3_K	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.Q3_K_L	Q3_K_L	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.Q3_K_S	Q3_K_S	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.IQ3_M	IQ3_M	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.IQ3_S	IQ3_S	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.IQ3_XS	IQ3_XS	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.IQ3_XXS	IQ3_XXS	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.Q2_K	Q2_K	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.Q2_K_S	Q2_K_S	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.IQ2_M	IQ2_M	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.IQ2_S	IQ2_S	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.IQ2_XS	IQ2_XS	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.IQ2_XXS	IQ2_XXS	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.IQ1_M	IQ1_M	-	⏳ Processing	🟢 IMatrix	-
Qwen2-57B-A14B-Instruct.IQ1_S	IQ1_S	-	⏳ Processing	🟢 IMatrix	-

Downloading using huggingface-cli

If you do not have hugginface-cli installed:

pip install -U "huggingface_hub[cli]"

Download the specific file you want:

huggingface-cli download legraphista/Qwen2-57B-A14B-Instruct-IMat-GGUF --include "Qwen2-57B-A14B-Instruct.Q8_0.gguf" --local-dir ./

If the model file is big, it has been split into multiple files. In order to download them all to a local folder, run:

huggingface-cli download legraphista/Qwen2-57B-A14B-Instruct-IMat-GGUF --include "Qwen2-57B-A14B-Instruct.Q8_0/*" --local-dir ./
# see FAQ for merging GGUF's

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Inference

Simple chat template

<|im_start|>system
You are a helpful assistant.<|im_end|>
<|im_start|>user
{user_prompt}<|im_end|>
<|im_start|>assistant
{assistant_response}<|im_end|>
<|im_start|>user
{next_user_prompt}<|im_end|>

Chat template with system prompt

<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{user_prompt}<|im_end|>
<|im_start|>assistant
{assistant_response}<|im_end|>
<|im_start|>user
{next_user_prompt}<|im_end|>

Llama.cpp

llama.cpp/main -m Qwen2-57B-A14B-Instruct.Q8_0.gguf --color -i -p "prompt here (according to the chat template)"

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FAQ

Why is the IMatrix not applied everywhere?

According to this investigation, it appears that lower quantizations are the only ones that benefit from the imatrix input (as per hellaswag results).

How do I merge a split GGUF?

1. Make sure you have gguf-split available
   • To get hold of gguf-split, navigate to https://github.com/ggerganov/llama.cpp/releases
   • Download the appropriate zip for your system from the latest release
   • Unzip the archive and you should be able to find gguf-split
2. Locate your GGUF chunks folder (ex: Qwen2-57B-A14B-Instruct.Q8_0)
3. Run gguf-split --merge Qwen2-57B-A14B-Instruct.Q8_0/Qwen2-57B-A14B-Instruct.Q8_0-00001-of-XXXXX.gguf Qwen2-57B-A14B-Instruct.Q8_0.gguf
   • Make sure to point gguf-split to the first chunk of the split.

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Got a suggestion? Ping me @legraphista!