metadata

base_model: Bin12345/AutoCoder_S_6.7B
inference: false
library_name: gguf
license: apache-2.0
pipeline_tag: text-generation
quantized_by: legraphista
tags:
  - quantized
  - GGUF
  - imatrix
  - quantization
  - imat
  - imatrix
  - static

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

AutoCoder_S_6.7B-IMat-GGUF

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?

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
Locate your GGUF chunks folder (ex: AutoCoder_S_6.7B.Q8_0)
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!