Hugging Face's logo

tensorblock
/
Meta-Llama-3-8B-Instruct-function-calling-GGUF

Transformers
GGUF
English
text-generation-inference
unsloth
llama
trl
llama 3
TensorBlock
GGUF
Inference Endpoints
conversational
Model card Files Community
Meta-Llama-3-8B-Instruct-function-calling-GGUF / README.md
morriszms's picture
morriszms
Upload folder using huggingface_hub
d509708 verified
preview code
|
raw
history blame
5.99 kB
metadata
language:
  - en
license: apache-2.0
tags:
  - text-generation-inference
  - transformers
  - unsloth
  - llama
  - trl
  - llama 3
  - TensorBlock
  - GGUF
datasets:
  - Trelis/function_calling_v3
base_model: Trelis/Meta-Llama-3-8B-Instruct-function-calling
TensorBlock

Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server

Trelis/Meta-Llama-3-8B-Instruct-function-calling - GGUF

This repo contains GGUF format model files for Trelis/Meta-Llama-3-8B-Instruct-function-calling.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

Prompt template 

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

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

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

Model file specification

Filename Quant type File Size Description
Meta-Llama-3-8B-Instruct-function-calling-Q2_K.gguf Q2_K 3.179 GB smallest, significant quality loss - not recommended for most purposes
Meta-Llama-3-8B-Instruct-function-calling-Q3_K_S.gguf Q3_K_S 3.664 GB very small, high quality loss
Meta-Llama-3-8B-Instruct-function-calling-Q3_K_M.gguf Q3_K_M 4.019 GB very small, high quality loss
Meta-Llama-3-8B-Instruct-function-calling-Q3_K_L.gguf Q3_K_L 4.322 GB small, substantial quality loss
Meta-Llama-3-8B-Instruct-function-calling-Q4_0.gguf Q4_0 4.661 GB legacy; small, very high quality loss - prefer using Q3_K_M
Meta-Llama-3-8B-Instruct-function-calling-Q4_K_S.gguf Q4_K_S 4.693 GB small, greater quality loss
Meta-Llama-3-8B-Instruct-function-calling-Q4_K_M.gguf Q4_K_M 4.921 GB medium, balanced quality - recommended
Meta-Llama-3-8B-Instruct-function-calling-Q5_0.gguf Q5_0 5.599 GB legacy; medium, balanced quality - prefer using Q4_K_M
Meta-Llama-3-8B-Instruct-function-calling-Q5_K_S.gguf Q5_K_S 5.599 GB large, low quality loss - recommended
Meta-Llama-3-8B-Instruct-function-calling-Q5_K_M.gguf Q5_K_M 5.733 GB large, very low quality loss - recommended
Meta-Llama-3-8B-Instruct-function-calling-Q6_K.gguf Q6_K 6.596 GB very large, extremely low quality loss
Meta-Llama-3-8B-Instruct-function-calling-Q8_0.gguf Q8_0 8.541 GB very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/Meta-Llama-3-8B-Instruct-function-calling-GGUF --include "Meta-Llama-3-8B-Instruct-function-calling-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/Meta-Llama-3-8B-Instruct-function-calling-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'