Downloads · 30 days
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legraphista/Yi-Coder-9B-Chat-IMat-GGUF
Yi-Coder-9B-Chat-IMat-GGUF is a text generation model from legraphista. Use it when you need the model to write or continue text. It is set up for gguf. The card lists the license as apache-2.0.
Llama.cpp imatrix quantization of 01-ai/Yi-Coder-9B-Chat
Downloads · 30 days
1.1K
6% of all-time downloads
All-time downloads
19.1K
Public
Repo size
134 GB
Likes
2
Public
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.gguf134 GB · 100%
From the Hugging Face model README
Llama.cpp imatrix quantization of 01-ai/Yi-Coder-9B-Chat
Original Model: 01-ai/Yi-Coder-9B-Chat
Original dtype: BF16 (bfloat16)
Quantized by: llama.cpp b3669
IMatrix dataset: here
Status: ✅ Available
Link: here
| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
|---|---|---|---|---|---|
| Yi-Coder-9B-Chat.Q8_0.gguf | Q8_0 | 9.38GB | ✅ Available | ⚪ Static | 📦 No |
| Yi-Coder-9B-Chat.Q6_K.gguf | Q6_K | 7.25GB | ✅ Available | ⚪ Static | 📦 No |
| Yi-Coder-9B-Chat.Q4_K.gguf | Q4_K | 5.33GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.Q3_K.gguf | Q3_K | 4.32GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.Q2_K.gguf | Q2_K | 3.35GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
|---|---|---|---|---|---|
| Yi-Coder-9B-Chat.BF16.gguf | BF16 | 17.66GB | ✅ Available | ⚪ Static | 📦 No |
| Yi-Coder-9B-Chat.FP16.gguf | F16 | 17.66GB | ✅ Available | ⚪ Static | 📦 No |
| Yi-Coder-9B-Chat.Q8_0.gguf | Q8_0 | 9.38GB | ✅ Available | ⚪ Static | 📦 No |
| Yi-Coder-9B-Chat.Q6_K.gguf | Q6_K | 7.25GB | ✅ Available | ⚪ Static | 📦 No |
| Yi-Coder-9B-Chat.Q5_K.gguf | Q5_K | 6.26GB | ✅ Available | ⚪ Static | 📦 No |
| Yi-Coder-9B-Chat.Q5_K_S.gguf | Q5_K_S | 6.11GB | ✅ Available | ⚪ Static | 📦 No |
| Yi-Coder-9B-Chat.Q4_K.gguf | Q4_K | 5.33GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.Q4_K_S.gguf | Q4_K_S | 5.07GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.IQ4_NL.gguf | IQ4_NL | 5.05GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.IQ4_XS.gguf | IQ4_XS | 4.79GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.Q3_K.gguf | Q3_K | 4.32GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.Q3_K_L.gguf | Q3_K_L | 4.69GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.Q3_K_S.gguf | Q3_K_S | 3.90GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.IQ3_M.gguf | IQ3_M | 4.06GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.IQ3_S.gguf | IQ3_S | 3.91GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.IQ3_XS.gguf | IQ3_XS | 3.72GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.IQ3_XXS.gguf | IQ3_XXS | 3.47GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.Q2_K.gguf | Q2_K | 3.35GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.Q2_K_S.gguf | Q2_K_S | 3.12GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.IQ2_M.gguf | IQ2_M | 3.10GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.IQ2_S.gguf | IQ2_S | 2.88GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.IQ2_XS.gguf | IQ2_XS | 2.71GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.IQ2_XXS.gguf | IQ2_XXS | 2.46GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.IQ1_M.gguf | IQ1_M | 2.18GB | ✅ Available | 🟢 IMatrix | 📦 No |
| Yi-Coder-9B-Chat.IQ1_S.gguf | IQ1_S | 2.01GB | ✅ Available | 🟢 IMatrix | 📦 No |
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-9B-Chat-IMat-GGUF --include "Yi-Coder-9B-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-9B-Chat-IMat-GGUF --include "Yi-Coder-9B-Chat.Q8_0/*" --local-dir ./
# see FAQ for merging GGUF's
<|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
<|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/main -m Yi-Coder-9B-Chat.Q8_0.gguf --color -i -p "prompt here (according to the chat template)"
According to this investigation, it appears that lower quantizations are the only ones that benefit from the imatrix input (as per hellaswag results).
gguf-split available
gguf-split, navigate to https://github.com/ggerganov/llama.cpp/releasesgguf-splitYi-Coder-9B-Chat.Q8_0)gguf-split --merge Yi-Coder-9B-Chat.Q8_0/Yi-Coder-9B-Chat.Q8_0-00001-of-XXXXX.gguf Yi-Coder-9B-Chat.Q8_0.gguf
gguf-split to the first chunk of the split.Got a suggestion? Ping me @legraphista!