Llama-3.2-1B-Instruct-IMat-GGUF

Llama.cpp imatrix quantization of meta-llama/Llama-3.2-1B-Instruct

Original Model: meta-llama/Llama-3.2-1B-Instruct
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-3.2-1B-Instruct.Q8_0.gguf Q8_0 1.32GB ✅ Available ⚪ Static 📦 No
Llama-3.2-1B-Instruct.Q6_K.gguf Q6_K 1.02GB ✅ Available ⚪ Static 📦 No
Llama-3.2-1B-Instruct.Q4_K.gguf Q4_K 807.69MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.Q3_K.gguf Q3_K 690.84MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.Q2_K.gguf Q2_K 580.87MB ✅ Available 🟢 IMatrix 📦 No

All Quants

Filename Quant type File Size Status Uses IMatrix Is Split
Llama-3.2-1B-Instruct.BF16.gguf BF16 2.48GB ✅ Available ⚪ Static 📦 No
Llama-3.2-1B-Instruct.FP16.gguf F16 2.48GB ✅ Available ⚪ Static 📦 No
Llama-3.2-1B-Instruct.Q8_0.gguf Q8_0 1.32GB ✅ Available ⚪ Static 📦 No
Llama-3.2-1B-Instruct.Q6_K.gguf Q6_K 1.02GB ✅ Available ⚪ Static 📦 No
Llama-3.2-1B-Instruct.Q5_K.gguf Q5_K 911.50MB ✅ Available ⚪ Static 📦 No
Llama-3.2-1B-Instruct.Q5_K_S.gguf Q5_K_S 892.56MB ✅ Available ⚪ Static 📦 No
Llama-3.2-1B-Instruct.Q4_K.gguf Q4_K 807.69MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.Q4_K_S.gguf Q4_K_S 775.65MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.IQ4_NL.gguf IQ4_NL 773.03MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.IQ4_XS.gguf IQ4_XS 743.14MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.Q3_K.gguf Q3_K 690.84MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.Q3_K_L.gguf Q3_K_L 732.52MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.Q3_K_S.gguf Q3_K_S 641.69MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.IQ3_M.gguf IQ3_M 657.29MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.IQ3_S.gguf IQ3_S 643.92MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.IQ3_XS.gguf IQ3_XS 621.11MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.IQ3_XXS.gguf IQ3_XXS 562.11MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.Q2_K.gguf Q2_K 580.87MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.Q2_K_S.gguf Q2_K_S 554.66MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.IQ2_M.gguf IQ2_M 515.45MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.IQ2_S.gguf IQ2_S 488.71MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.IQ2_XS.gguf IQ2_XS 475.87MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.IQ2_XXS.gguf IQ2_XXS 447.03MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.IQ1_M.gguf IQ1_M 413.61MB ✅ Available 🟢 IMatrix 📦 No
Llama-3.2-1B-Instruct.IQ1_S.gguf IQ1_S 393.55MB ✅ 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-3.2-1B-Instruct-IMat-GGUF --include "Llama-3.2-1B-Instruct.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-3.2-1B-Instruct-IMat-GGUF --include "Llama-3.2-1B-Instruct.Q8_0/*" --local-dir ./
# see FAQ for merging GGUF's

Inference

Simple chat template

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

Cutting Knowledge Date: December 2023
Today Date: 26 Jul 2024

<|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|>

Chat template with system prompt

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

Cutting Knowledge Date: December 2023
Today Date: 26 Jul 2024

{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 Llama-3.2-1B-Instruct.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-3.2-1B-Instruct.Q8_0)
  3. Run gguf-split --merge Llama-3.2-1B-Instruct.Q8_0/Llama-3.2-1B-Instruct.Q8_0-00001-of-XXXXX.gguf Llama-3.2-1B-Instruct.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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