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AutoCoder-IMat-GGUF

Llama.cpp imatrix quantization of Bin12345/AutoCoder

Original Model: Bin12345/AutoCoder
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.Q8_0.gguf Q8_0 35.43GB ✅ Available ⚪ Static 📦 No
AutoCoder.Q6_K.gguf Q6_K 27.36GB ✅ Available ⚪ Static 📦 No
AutoCoder.Q4_K.gguf Q4_K 19.94GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder.Q3_K.gguf Q3_K 16.09GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder.Q2_K.gguf Q2_K 12.36GB ✅ Available 🟢 IMatrix 📦 No

All Quants

Filename Quant type File Size Status Uses IMatrix Is Split
AutoCoder.BF16/* BF16 66.69GB ✅ Available ⚪ Static ✂ Yes
AutoCoder.FP16/* F16 66.69GB ✅ Available ⚪ Static ✂ Yes
AutoCoder.Q5_K.gguf Q5_K 23.54GB ✅ Available ⚪ Static 📦 No
AutoCoder.Q5_K_S.gguf Q5_K_S 22.96GB ✅ Available ⚪ Static 📦 No
AutoCoder.Q4_K_S.gguf Q4_K_S 18.94GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder.Q3_K_L.gguf Q3_K_L 17.56GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder.Q3_K_S.gguf Q3_K_S 14.42GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder.Q2_K_S.gguf Q2_K_S 11.39GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder.IQ4_NL.gguf IQ4_NL 18.88GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder.IQ4_XS.gguf IQ4_XS 17.86GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder.IQ3_M.gguf IQ3_M 15.03GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder.IQ3_S.gguf IQ3_S 14.48GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder.IQ3_XS.gguf IQ3_XS 13.71GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder.IQ3_XXS.gguf IQ3_XXS 12.85GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder.IQ2_M.gguf IQ2_M 11.36GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder.IQ2_S.gguf IQ2_S 10.48GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder.IQ2_XS.gguf IQ2_XS 9.91GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder.IQ2_XXS.gguf IQ2_XXS 8.92GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder.IQ1_M.gguf IQ1_M 7.82GB ✅ Available 🟢 IMatrix 📦 No
AutoCoder.IQ1_S.gguf IQ1_S 7.16GB ✅ 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-IMat-GGUF --include "AutoCoder.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-IMat-GGUF --include "AutoCoder.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.<|EOT|>
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.<|EOT|>
Human: What about solving an 2x + 3 = 7 equation?
Assistant: 

Llama.cpp

llama.cpp/main -m AutoCoder.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.Q8_0)
  3. Run gguf-split --merge AutoCoder.Q8_0/AutoCoder.Q8_0-00001-of-XXXXX.gguf AutoCoder.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
33.3B params
Architecture
llama

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

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Base model

Bin12345/AutoCoder
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Collection including legraphista/AutoCoder-IMat-GGUF