README.md

metadata

base_model: TechxGenus/Yi-9B-Coder
inference: false
library_name: gguf
license: apache-2.0
pipeline_tag: text-generation
quantized_by: legraphista
tags:
  - code
  - llama
  - quantized
  - GGUF
  - quantization
  - imat
  - imatrix
  - static
  - 16bit
  - 8bit
  - 6bit
  - 5bit
  - 4bit
  - 3bit
  - 2bit
  - 1bit

Yi-9B-Coder-IMat-GGUF

Llama.cpp imatrix quantization of TechxGenus/Yi-9B-Coder

Original Model: TechxGenus/Yi-9B-Coder
Original dtype: BF16 (bfloat16)
Quantized by: llama.cpp b3248
IMatrix dataset: here

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

---

Files

IMatrix

Status: ✅ Available
Link: here

Common Quants

Filename	Quant type	File Size	Status	Uses IMatrix	Is Split
Yi-9B-Coder.Q8_0.gguf	Q8_0	9.38GB	✅ Available	⚪ Static	📦 No
Yi-9B-Coder.Q6_K.gguf	Q6_K	7.25GB	✅ Available	⚪ Static	📦 No
Yi-9B-Coder.Q4_K.gguf	Q4_K	5.33GB	✅ Available	🟢 IMatrix	📦 No
Yi-9B-Coder.Q3_K.gguf	Q3_K	4.32GB	✅ Available	🟢 IMatrix	📦 No
Yi-9B-Coder.Q2_K.gguf	Q2_K	3.35GB	✅ Available	🟢 IMatrix	📦 No

All Quants

Filename	Quant type	File Size	Status	Uses IMatrix	Is Split
Yi-9B-Coder.BF16	BF16	-	⏳ Processing	⚪ Static	-
Yi-9B-Coder.FP16.gguf	F16	17.66GB	✅ Available	⚪ Static	📦 No
Yi-9B-Coder.Q8_0.gguf	Q8_0	9.38GB	✅ Available	⚪ Static	📦 No
Yi-9B-Coder.Q6_K.gguf	Q6_K	7.25GB	✅ Available	⚪ Static	📦 No
Yi-9B-Coder.Q5_K.gguf	Q5_K	6.26GB	✅ Available	⚪ Static	📦 No
Yi-9B-Coder.Q5_K_S.gguf	Q5_K_S	6.11GB	✅ Available	⚪ Static	📦 No
Yi-9B-Coder.Q4_K.gguf	Q4_K	5.33GB	✅ Available	🟢 IMatrix	📦 No
Yi-9B-Coder.Q4_K_S.gguf	Q4_K_S	5.07GB	✅ Available	🟢 IMatrix	📦 No
Yi-9B-Coder.IQ4_NL.gguf	IQ4_NL	5.05GB	✅ Available	🟢 IMatrix	📦 No
Yi-9B-Coder.IQ4_XS	IQ4_XS	-	⏳ Processing	🟢 IMatrix	-
Yi-9B-Coder.Q3_K.gguf	Q3_K	4.32GB	✅ Available	🟢 IMatrix	📦 No
Yi-9B-Coder.Q3_K_L.gguf	Q3_K_L	4.69GB	✅ Available	🟢 IMatrix	📦 No
Yi-9B-Coder.Q3_K_S.gguf	Q3_K_S	3.90GB	✅ Available	🟢 IMatrix	📦 No
Yi-9B-Coder.IQ3_M	IQ3_M	-	⏳ Processing	🟢 IMatrix	-
Yi-9B-Coder.IQ3_S	IQ3_S	-	⏳ Processing	🟢 IMatrix	-
Yi-9B-Coder.IQ3_XS	IQ3_XS	-	⏳ Processing	🟢 IMatrix	-
Yi-9B-Coder.IQ3_XXS	IQ3_XXS	-	⏳ Processing	🟢 IMatrix	-
Yi-9B-Coder.Q2_K.gguf	Q2_K	3.35GB	✅ Available	🟢 IMatrix	📦 No
Yi-9B-Coder.Q2_K_S.gguf	Q2_K_S	3.12GB	✅ Available	🟢 IMatrix	📦 No
Yi-9B-Coder.IQ2_M	IQ2_M	-	⏳ Processing	🟢 IMatrix	-
Yi-9B-Coder.IQ2_S	IQ2_S	-	⏳ Processing	🟢 IMatrix	-
Yi-9B-Coder.IQ2_XS	IQ2_XS	-	⏳ Processing	🟢 IMatrix	-
Yi-9B-Coder.IQ2_XXS	IQ2_XXS	-	⏳ Processing	🟢 IMatrix	-
Yi-9B-Coder.IQ1_M	IQ1_M	-	⏳ Processing	🟢 IMatrix	-
Yi-9B-Coder.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/Yi-9B-Coder-IMat-GGUF --include "Yi-9B-Coder.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-9B-Coder-IMat-GGUF --include "Yi-9B-Coder.Q8_0/*" --local-dir ./
# see FAQ for merging GGUF's

---

Inference

Llama.cpp

llama.cpp/main -m Yi-9B-Coder.Q8_0.gguf --color -i -p "prompt here"

---

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-9B-Coder.Q8_0)
3. Run gguf-split --merge Yi-9B-Coder.Q8_0/Yi-9B-Coder.Q8_0-00001-of-XXXXX.gguf Yi-9B-Coder.Q8_0.gguf
   • Make sure to point gguf-split to the first chunk of the split.

---

Got a suggestion? Ping me @legraphista!