Instructions to use ToddLLM/OrpoLlama-3-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ToddLLM/OrpoLlama-3-8B with Transformers:

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

pipe = pipeline("text-generation", model="ToddLLM/OrpoLlama-3-8B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("ToddLLM/OrpoLlama-3-8B")
model = AutoModelForMultimodalLM.from_pretrained("ToddLLM/OrpoLlama-3-8B")
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]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ToddLLM/OrpoLlama-3-8B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ToddLLM/OrpoLlama-3-8B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ToddLLM/OrpoLlama-3-8B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ToddLLM/OrpoLlama-3-8B

SGLang

How to use ToddLLM/OrpoLlama-3-8B 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 "ToddLLM/OrpoLlama-3-8B" \
    --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": "ToddLLM/OrpoLlama-3-8B",
		"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 "ToddLLM/OrpoLlama-3-8B" \
        --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": "ToddLLM/OrpoLlama-3-8B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use ToddLLM/OrpoLlama-3-8B with Docker Model Runner:
```
docker model run hf.co/ToddLLM/OrpoLlama-3-8B
```

OrpoLlama-3-8B

Commit History

Upload tokenizer

672e2d1
verified

Todd Deshane commited on Apr 19, 2024

Upload LlamaForCausalLM

9f197ea
verified

Todd Deshane commited on Apr 19, 2024

initial commit

5760a81
verified

Todd Deshane commited on Apr 19, 2024

Commit History

Upload tokenizer 672e2d1 verified

Upload LlamaForCausalLM 9f197ea verified

initial commit 5760a81 verified

Upload tokenizer

672e2d1
verified

Upload LlamaForCausalLM

9f197ea
verified

initial commit

5760a81
verified