Text Generation
MLX
Safetensors
PyTorch
English
llama
facebook
meta
llama-3
groq
tool-use
function-calling
conversational
How to use from
MLX LMRun an OpenAI-compatible server
# Install MLX LM
uv tool install mlx-lm# Start the server
mlx_lm.server --model "mlx-community/Llama-3-Groq-8B-Tool-Use-bf16"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "mlx-community/Llama-3-Groq-8B-Tool-Use-bf16",
"messages": [
{"role": "user", "content": "Hello"}
]
}'Quick Links
mlx-community/Llama-3-Groq-8B-Tool-Use-bf16
The Model mlx-community/Llama-3-Groq-8B-Tool-Use-bf16 was converted to MLX format from Groq/Llama-3-Groq-8B-Tool-Use using mlx-lm version 0.15.2.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Llama-3-Groq-8B-Tool-Use-bf16")
response = generate(model, tokenizer, prompt="hello", verbose=True)
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Model size
8B params
Tensor type
BF16
·
Hardware compatibility
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Generate or start a chat session
# Install MLX LM uv tool install mlx-lm# Interactive chat REPL mlx_lm.chat --model "mlx-community/Llama-3-Groq-8B-Tool-Use-bf16"