Llama-Guard-3-1B-IMat-GGUF

Llama.cpp imatrix quantization of meta-llama/Llama-Guard-3-1B

Original Model: meta-llama/Llama-Guard-3-1B
Original dtype: BF16 (bfloat16)
Quantized by: llama.cpp b3825
IMatrix dataset: here


Files

IMatrix

Status: ✅ Available
Link: here

Common Quants

Filename Quant type File Size Status Uses IMatrix Is Split
Llama-Guard-3-1B.Q8_0.gguf Q8_0 1.60GB ✅ Available ⚪ Static 📦 No
Llama-Guard-3-1B.Q6_K.gguf Q6_K 1.24GB ✅ Available ⚪ Static 📦 No
Llama-Guard-3-1B.Q4_K.gguf Q4_K 955.44MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.Q3_K.gguf Q3_K 803.71MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.Q2_K.gguf Q2_K 667.06MB ✅ Available 🟢 IMatrix 📦 No

All Quants

Filename Quant type File Size Status Uses IMatrix Is Split
Llama-Guard-3-1B.BF16.gguf BF16 3.00GB ✅ Available ⚪ Static 📦 No
Llama-Guard-3-1B.FP16.gguf F16 3.00GB ✅ Available ⚪ Static 📦 No
Llama-Guard-3-1B.Q8_0.gguf Q8_0 1.60GB ✅ Available ⚪ Static 📦 No
Llama-Guard-3-1B.Q6_K.gguf Q6_K 1.24GB ✅ Available ⚪ Static 📦 No
Llama-Guard-3-1B.Q5_K.gguf Q5_K 1.09GB ✅ Available ⚪ Static 📦 No
Llama-Guard-3-1B.Q5_K_S.gguf Q5_K_S 1.07GB ✅ Available ⚪ Static 📦 No
Llama-Guard-3-1B.Q4_K.gguf Q4_K 955.44MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.Q4_K_S.gguf Q4_K_S 923.40MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.IQ4_NL.gguf IQ4_NL 920.78MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.IQ4_XS.gguf IQ4_XS 882.68MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.Q3_K.gguf Q3_K 803.71MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.Q3_K_L.gguf Q3_K_L 845.39MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.Q3_K_S.gguf Q3_K_S 754.56MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.IQ3_M.gguf IQ3_M 770.15MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.IQ3_S.gguf IQ3_S 756.78MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.IQ3_XS.gguf IQ3_XS 733.98MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.IQ3_XXS.gguf IQ3_XXS 674.97MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.Q2_K.gguf Q2_K 667.06MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.Q2_K_S.gguf Q2_K_S 640.85MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.IQ2_M.gguf IQ2_M 628.31MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.IQ2_S.gguf IQ2_S 601.57MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.IQ2_XS.gguf IQ2_XS 562.05MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.IQ2_XXS.gguf IQ2_XXS 533.22MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.IQ1_M.gguf IQ1_M 499.79MB ✅ Available 🟢 IMatrix 📦 No
Llama-Guard-3-1B.IQ1_S.gguf IQ1_S 479.74MB ✅ 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-3-1B-IMat-GGUF --include "Llama-Guard-3-1B.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-3-1B-IMat-GGUF --include "Llama-Guard-3-1B.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.
<END UNSAFE CONTENT CATEGORIES>

<BEGIN CONVERSATION>

<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-3-1B.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-3-1B.Q8_0)
  3. Run gguf-split --merge Llama-Guard-3-1B.Q8_0/Llama-Guard-3-1B.Q8_0-00001-of-XXXXX.gguf Llama-Guard-3-1B.Q8_0.gguf
    • Make sure to point gguf-split to the first chunk of the split.

Got a suggestion? Ping me @legraphista!

Downloads last month
290
GGUF
Model size
1.5B params
Architecture
llama

1-bit

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

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

Model tree for legraphista/Llama-Guard-3-1B-IMat-GGUF

Quantized
(15)
this model