Yi-Coder-1.5B-Chat-IMat-GGUF

Llama.cpp imatrix quantization of 01-ai/Yi-Coder-1.5B-Chat

Original Model: 01-ai/Yi-Coder-1.5B-Chat
Original dtype: BF16 (bfloat16)
Quantized by: llama.cpp b3669
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
Yi-Coder-1.5B-Chat.Q8_0.gguf	Q8_0	1.57GB	✅ Available	⚪ Static	📦 No
Yi-Coder-1.5B-Chat.Q6_K.gguf	Q6_K	1.28GB	✅ Available	⚪ Static	📦 No
Yi-Coder-1.5B-Chat.Q4_K.gguf	Q4_K	963.67MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.Q3_K.gguf	Q3_K	785.72MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.Q2_K.gguf	Q2_K	634.70MB	✅ Available	🟢 IMatrix	📦 No

All Quants

Filename	Quant type	File Size	Status	Uses IMatrix	Is Split
Yi-Coder-1.5B-Chat.BF16.gguf	BF16	2.95GB	✅ Available	⚪ Static	📦 No
Yi-Coder-1.5B-Chat.FP16.gguf	F16	2.95GB	✅ Available	⚪ Static	📦 No
Yi-Coder-1.5B-Chat.Q8_0.gguf	Q8_0	1.57GB	✅ Available	⚪ Static	📦 No
Yi-Coder-1.5B-Chat.Q6_K.gguf	Q6_K	1.28GB	✅ Available	⚪ Static	📦 No
Yi-Coder-1.5B-Chat.Q5_K.gguf	Q5_K	1.10GB	✅ Available	⚪ Static	📦 No
Yi-Coder-1.5B-Chat.Q5_K_S.gguf	Q5_K_S	1.05GB	✅ Available	⚪ Static	📦 No
Yi-Coder-1.5B-Chat.Q4_K.gguf	Q4_K	963.67MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.Q4_K_S.gguf	Q4_K_S	904.18MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.IQ4_NL.gguf	IQ4_NL	866.16MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.IQ4_XS.gguf	IQ4_XS	832.57MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.Q3_K.gguf	Q3_K	785.72MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.Q3_K_L.gguf	Q3_K_L	826.04MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.Q3_K_S.gguf	Q3_K_S	723.41MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.IQ3_M.gguf	IQ3_M	754.38MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.IQ3_S.gguf	IQ3_S	723.41MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.IQ3_XS.gguf	IQ3_XS	694.95MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.IQ3_XXS.gguf	IQ3_XXS	653.90MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.Q2_K.gguf	Q2_K	634.70MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.Q2_K_S.gguf	Q2_K_S	618.48MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.IQ2_M.gguf	IQ2_M	624.80MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.IQ2_S.gguf	IQ2_S	601.60MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.IQ2_XS.gguf	IQ2_XS	563.91MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.IQ2_XXS.gguf	IQ2_XXS	537.57MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.IQ1_M.gguf	IQ1_M	508.57MB	✅ Available	🟢 IMatrix	📦 No
Yi-Coder-1.5B-Chat.IQ1_S.gguf	IQ1_S	491.17MB	✅ Available	🟢 IMatrix	📦 No

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/Yi-Coder-1.5B-Chat-IMat-GGUF --include "Yi-Coder-1.5B-Chat.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/Yi-Coder-1.5B-Chat-IMat-GGUF --include "Yi-Coder-1.5B-Chat.Q8_0/*" --local-dir ./
# see FAQ for merging GGUF's

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Inference

Simple chat template

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

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|>
<|im_start|>assistant

Llama.cpp

llama.cpp/main -m Yi-Coder-1.5B-Chat.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: Yi-Coder-1.5B-Chat.Q8_0)
3. Run gguf-split --merge Yi-Coder-1.5B-Chat.Q8_0/Yi-Coder-1.5B-Chat.Q8_0-00001-of-XXXXX.gguf Yi-Coder-1.5B-Chat.Q8_0.gguf
   • Make sure to point gguf-split to the first chunk of the split.

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