Instructions to use Groq/Llama-3-Groq-70B-Tool-Use with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Groq/Llama-3-Groq-70B-Tool-Use with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Groq/Llama-3-Groq-70B-Tool-Use")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Groq/Llama-3-Groq-70B-Tool-Use")
model = AutoModelForCausalLM.from_pretrained("Groq/Llama-3-Groq-70B-Tool-Use")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Groq/Llama-3-Groq-70B-Tool-Use with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Groq/Llama-3-Groq-70B-Tool-Use"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Groq/Llama-3-Groq-70B-Tool-Use",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Groq/Llama-3-Groq-70B-Tool-Use

SGLang

How to use Groq/Llama-3-Groq-70B-Tool-Use with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Groq/Llama-3-Groq-70B-Tool-Use" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Groq/Llama-3-Groq-70B-Tool-Use",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Groq/Llama-3-Groq-70B-Tool-Use" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Groq/Llama-3-Groq-70B-Tool-Use",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Groq/Llama-3-Groq-70B-Tool-Use with Docker Model Runner:
```
docker model run hf.co/Groq/Llama-3-Groq-70B-Tool-Use
```

Issue with Updated Model Weights

by gyuuuna - opened Jul 23, 2024

Discussion

gyuuuna

Jul 23, 2024

Issue with Updated Model Weights

I've recently downloaded the model weights and noticed something unusual.
The total weight size has decreased compared with previous version. (current version: feat: update to better 70b dpo tune)
I attempted to load the new model, but the model does not run.
This reduction in size seems strange and I'm unsure if this is an error or an intended change.

Any insights or suggestions to resolve this would be greatly appreciated.
Thank you!