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

sourceHugging Facellama3.1updated 2y agoView on Hugging Face
5likes3.5kdownloads
Model Card

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

FilenameQuant typeFile SizeStatusUses IMatrixIs Split
Llama-Guard-3-8B.Q8_0.ggufQ8_08.54GB✅ Available⚪ Static📦 No
Llama-Guard-3-8B.Q6_K.ggufQ6_K6.60GB✅ Available⚪ Static📦 No
Llama-Guard-3-8B.Q4_K.ggufQ4_K4.92GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.Q3_K.ggufQ3_K4.02GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.Q2_K.ggufQ2_K3.18GB✅ Available🟢 IMatrix📦 No

All Quants

FilenameQuant typeFile SizeStatusUses IMatrixIs Split
Llama-Guard-3-8B.BF16.ggufBF1616.07GB✅ Available⚪ Static📦 No
Llama-Guard-3-8B.FP16.ggufF1616.07GB✅ Available⚪ Static📦 No
Llama-Guard-3-8B.Q8_0.ggufQ8_08.54GB✅ Available⚪ Static📦 No
Llama-Guard-3-8B.Q6_K.ggufQ6_K6.60GB✅ Available⚪ Static📦 No
Llama-Guard-3-8B.Q5_K.ggufQ5_K5.73GB✅ Available⚪ Static📦 No
Llama-Guard-3-8B.Q5_K_S.ggufQ5KS5.60GB✅ Available⚪ Static📦 No
Llama-Guard-3-8B.Q4_K.ggufQ4_K4.92GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.Q4_K_S.ggufQ4KS4.69GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.IQ4_NL.ggufIQ4_NL4.68GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.IQ4_XS.ggufIQ4_XS4.45GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.Q3_K.ggufQ3_K4.02GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.Q3_K_L.ggufQ3KL4.32GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.Q3_K_S.ggufQ3KS3.66GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.IQ3_M.ggufIQ3_M3.78GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.IQ3_S.ggufIQ3_S3.68GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.IQ3_XS.ggufIQ3_XS3.52GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.IQ3_XXS.ggufIQ3_XXS3.27GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.Q2_K.ggufQ2_K3.18GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.Q2_K_S.ggufQ2KS2.99GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.IQ2_M.ggufIQ2_M2.95GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.IQ2_S.ggufIQ2_S2.76GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.IQ2_XS.ggufIQ2_XS2.61GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.IQ2_XXS.ggufIQ2_XXS2.40GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.IQ1_M.ggufIQ1_M2.16GB✅ Available🟢 IMatrix📦 No
Llama-Guard-3-8B.IQ1_S.ggufIQ1_S2.02GB✅ 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. 1.Make sure you have gguf-split available
  2. 2.To get hold of gguf-split, navigate to https://github.com/ggerganov/llama.cpp/releases
  3. 3.Download the appropriate zip for your system from the latest release
  4. 4.Unzip the archive and you should be able to find gguf-split
  5. 5.Locate your GGUF chunks folder (ex: Llama-Guard-3-8B.Q8_0)
  6. 6.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
  7. 7.Make sure to point gguf-split to the first chunk of the split.

Got a suggestion? Ping me @legraphista!