ModelHub XC e0aa2e10d1 初始化项目,由ModelHub XC社区提供模型
Model: legraphista/Meta-Llama-3-8B-Instruct-abliterated-v3-IMat-GGUF
Source: Original Platform
2026-07-25 17:14:10 +08:00

base_model, inference, library_name, license, pipeline_tag, quantized_by, tags
base_model inference library_name license pipeline_tag quantized_by tags
failspy/Meta-Llama-3-8B-Instruct-abliterated-v3 false gguf llama3 text-generation legraphista
quantized
GGUF
imatrix
quantization
imat
imatrix
static
16bit
8bit
6bit
5bit
4bit
3bit
2bit
1bit

Meta-Llama-3-8B-Instruct-abliterated-v3-IMat-GGUF

Llama.cpp imatrix quantization of failspy/Meta-Llama-3-8B-Instruct-abliterated-v3

Original Model: failspy/Meta-Llama-3-8B-Instruct-abliterated-v3
Original dtype: BF16 (bfloat16)
Quantized by: llama.cpp b3058
IMatrix dataset: here


Files

IMatrix

Status: ✅ Available
Link: here

Common Quants

Filename Quant type File Size Status Uses IMatrix Is Split
Meta-Llama-3-8B-Instruct-abliterated-v3.Q8_0.gguf Q8_0 8.54GB ✅ Available ⚪ Static 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.Q6_K.gguf Q6_K 6.60GB ✅ Available ⚪ Static 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.Q4_K.gguf Q4_K 4.92GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.Q3_K.gguf Q3_K 4.02GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.Q2_K.gguf Q2_K 3.18GB ✅ Available 🟢 IMatrix 📦 No

All Quants

Filename Quant type File Size Status Uses IMatrix Is Split
Meta-Llama-3-8B-Instruct-abliterated-v3.BF16.gguf BF16 16.07GB ✅ Available ⚪ Static 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.FP16.gguf F16 16.07GB ✅ Available ⚪ Static 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.Q8_0.gguf Q8_0 8.54GB ✅ Available ⚪ Static 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.Q6_K.gguf Q6_K 6.60GB ✅ Available ⚪ Static 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.Q5_K.gguf Q5_K 5.73GB ✅ Available ⚪ Static 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.Q5_K_S.gguf Q5_K_S 5.60GB ✅ Available ⚪ Static 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.Q4_K.gguf Q4_K 4.92GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.Q4_K_S.gguf Q4_K_S 4.69GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.IQ4_NL.gguf IQ4_NL 4.68GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.IQ4_XS.gguf IQ4_XS 4.45GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.Q3_K.gguf Q3_K 4.02GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.Q3_K_L.gguf Q3_K_L 4.32GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.Q3_K_S.gguf Q3_K_S 3.66GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.IQ3_M.gguf IQ3_M 3.78GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.IQ3_S.gguf IQ3_S 3.68GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.IQ3_XS.gguf IQ3_XS 3.52GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.IQ3_XXS.gguf IQ3_XXS 3.27GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.Q2_K.gguf Q2_K 3.18GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.Q2_K_S.gguf Q2_K_S 2.99GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.IQ2_M.gguf IQ2_M 2.95GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.IQ2_S.gguf IQ2_S 2.76GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.IQ2_XS.gguf IQ2_XS 2.61GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.IQ2_XXS.gguf IQ2_XXS 2.40GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.IQ1_M.gguf IQ1_M 2.16GB ✅ Available 🟢 IMatrix 📦 No
Meta-Llama-3-8B-Instruct-abliterated-v3.IQ1_S.gguf IQ1_S 2.02GB ✅ 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/Meta-Llama-3-8B-Instruct-abliterated-v3-IMat-GGUF --include "Meta-Llama-3-8B-Instruct-abliterated-v3.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/Meta-Llama-3-8B-Instruct-abliterated-v3-IMat-GGUF --include "Meta-Llama-3-8B-Instruct-abliterated-v3.Q8_0/*" --local-dir ./
# see FAQ for merging GGUF's

Inference

Simple chat template

<|begin_of_text|><|start_header_id|>user<|end_header_id|>

{user_prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>

{assistant_response}<|eot_id|><|start_header_id|>user<|end_header_id|>

{next_user_prompt}<|eot_id|>

Chat template with system prompt

<|begin_of_text|><|start_header_id|>system<|end_header_id|>

{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>

{user_prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>

{assistant_response}<|eot_id|><|start_header_id|>user<|end_header_id|>

{next_user_prompt}<|eot_id|>

Llama.cpp

llama.cpp/main -m Meta-Llama-3-8B-Instruct-abliterated-v3.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: Meta-Llama-3-8B-Instruct-abliterated-v3.Q8_0)
  3. Run gguf-split --merge Meta-Llama-3-8B-Instruct-abliterated-v3.Q8_0/Meta-Llama-3-8B-Instruct-abliterated-v3.Q8_0-00001-of-XXXXX.gguf Meta-Llama-3-8B-Instruct-abliterated-v3.Q8_0.gguf
    • Make sure to point gguf-split to the first chunk of the split.

Got a suggestion? Ping me @legraphista!

Description
Model synced from source: legraphista/Meta-Llama-3-8B-Instruct-abliterated-v3-IMat-GGUF
Readme 152 KiB