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AutoCoder_S_6.7B-IMat-GGUF

Llama.cpp imatrix quantization of Bin12345/AutoCoder_S_6.7B

Original Model: Bin12345/AutoCoder_S_6.7B
Original dtype: BF16 (bfloat16)
Quantized by: llama.cpp b3010
IMatrix dataset: here


Files

IMatrix

Status: ✅ Available
Link: here

Common Quants

Filename Quant type File Size Status Uses IMatrix Is Split
AutoCoder_S_6.7B.Q8_0.gguf Q8_0 7.16GB ✅ Available ⚪ Static 📦 No
AutoCoder_S_6.7B.Q6_K.gguf Q6_K 5.53GB ✅ Available ⚪ Static 📦 No
AutoCoder_S_6.7B.Q4_K.gguf Q4_K 4.08GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder_S_6.7B.Q3_K.gguf Q3_K 3.30GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder_S_6.7B.Q2_K.gguf Q2_K 2.53GB ✅ Available 🟢 IMatrix 📦 No

All Quants

Filename Quant type File Size Status Uses IMatrix Is Split
AutoCoder_S_6.7B.BF16.gguf BF16 13.48GB ✅ Available ⚪ Static 📦 No
AutoCoder_S_6.7B.FP16.gguf F16 13.48GB ✅ Available ⚪ Static 📦 No
AutoCoder_S_6.7B.Q5_K.gguf Q5_K 4.79GB ✅ Available ⚪ Static 📦 No
AutoCoder_S_6.7B.Q5_K_S.gguf Q5_K_S 4.65GB ✅ Available ⚪ Static 📦 No
AutoCoder_S_6.7B.Q4_K_S.gguf Q4_K_S 3.86GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder_S_6.7B.Q3_K_L.gguf Q3_K_L 3.60GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder_S_6.7B.Q3_K_S.gguf Q3_K_S 2.95GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder_S_6.7B.Q2_K_S.gguf Q2_K_S 2.32GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder_S_6.7B.IQ4_NL.gguf IQ4_NL 3.83GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder_S_6.7B.IQ4_XS.gguf IQ4_XS 3.62GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder_S_6.7B.IQ3_M.gguf IQ3_M 3.12GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder_S_6.7B.IQ3_S.gguf IQ3_S 2.95GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder_S_6.7B.IQ3_XS.gguf IQ3_XS 2.80GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder_S_6.7B.IQ3_XXS.gguf IQ3_XXS 2.59GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder_S_6.7B.IQ2_M.gguf IQ2_M 2.36GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder_S_6.7B.IQ2_S.gguf IQ2_S 2.20GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder_S_6.7B.IQ2_XS.gguf IQ2_XS 2.04GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder_S_6.7B.IQ2_XXS.gguf IQ2_XXS 1.86GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder_S_6.7B.IQ1_M.gguf IQ1_M 1.65GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder_S_6.7B.IQ1_S.gguf IQ1_S 1.53GB ✅ 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/AutoCoder_S_6.7B-IMat-GGUF --include "AutoCoder_S_6.7B.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/AutoCoder_S_6.7B-IMat-GGUF --include "AutoCoder_S_6.7B.Q8_0/*" --local-dir ./
# see FAQ for merging GGUF's

Inference

Simple chat template

Human: Can you provide ways to eat combinations of bananas and dragonfruits?
Assistant: Sure! Here are some ways to eat bananas and dragonfruits together:
 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey.
 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey.<|end▁of▁sentence|>
Human: What about solving an 2x + 3 = 7 equation?
Assistant: 

Chat template with system prompt

You are a helpful AI.
Human: Can you provide ways to eat combinations of bananas and dragonfruits?
Assistant: Sure! Here are some ways to eat bananas and dragonfruits together:
 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey.
 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey.<|end▁of▁sentence|>
Human: What about solving an 2x + 3 = 7 equation?
Assistant: 

Llama.cpp

llama.cpp/main -m AutoCoder_S_6.7B.Q8_0.gguf --color -i -p "prompt here (according to the chat template)"

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
  2. Locate your GGUF chunks folder (ex: AutoCoder_S_6.7B.Q8_0)
  3. Run gguf-split --merge AutoCoder_S_6.7B.Q8_0/AutoCoder_S_6.7B.Q8_0-00001-of-XXXXX.gguf AutoCoder_S_6.7B.Q8_0.gguf
    • Make sure to point gguf-split to the first chunk of the split.

Got a suggestion? Ping me @legraphista!

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GGUF
Model size
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Architecture
llama

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Inference Examples
Inference API (serverless) has been turned off for this model.

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