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Llama-Guard-3-8B-IMat-GGUF

Llama.cpp imatrix quantization of meta-llama/Llama-Guard-3-8B

Original Model: meta-llama/Llama-Guard-3-8B
Original dtype: BF16 (bfloat16)
Quantized by: llama.cpp b3447
IMatrix dataset: here


Files

IMatrix

Status: ✅ Available
Link: here

Common Quants

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

All Quants

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

Inference

Simple chat template

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

Task: Check if there is unsafe content in 'User' messages in conversations according our safety policy with the below categories.

<BEGIN UNSAFE CONTENT CATEGORIES>
S1: Violent Crimes.
S2: Non-Violent Crimes.
S3: Sex Crimes.
S4: Child Exploitation.
S5: Defamation.
S6: Specialized Advice.
S7: Privacy.
S8: Intellectual Property.
S9: Indiscriminate Weapons.
S10: Hate.
S11: Self-Harm.
S12: Sexual Content.
S13: Elections.
S14: Code Interpreter Abuse.
<END UNSAFE CONTENT CATEGORIES>

<BEGIN CONVERSATION>

User: {user_prompt}

Agent: {assistant_response}

User: {next_user_prompt}

<END CONVERSATION>

Provide your safety assessment for ONLY THE LAST User message in the above conversation:
 - First line must read 'safe' or 'unsafe'.
 - If unsafe, a second line must include a comma-separated list of violated categories.<|eot_id|><|start_header_id|>assistant<|end_header_id|>

Llama.cpp

llama.cpp/main -m Llama-Guard-3-8B.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: Llama-Guard-3-8B.Q8_0)
  3. Run gguf-split --merge Llama-Guard-3-8B.Q8_0/Llama-Guard-3-8B.Q8_0-00001-of-XXXXX.gguf Llama-Guard-3-8B.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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llama

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

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