Instructions to use titan087/Llama3-70B-ShiningValiant2-exl2-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use titan087/Llama3-70B-ShiningValiant2-exl2-4b with Transformers:

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

pipe = pipeline("text-generation", model="titan087/Llama3-70B-ShiningValiant2-exl2-4b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("titan087/Llama3-70B-ShiningValiant2-exl2-4b")
model = AutoModelForCausalLM.from_pretrained("titan087/Llama3-70B-ShiningValiant2-exl2-4b")
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

vLLM

How to use titan087/Llama3-70B-ShiningValiant2-exl2-4b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "titan087/Llama3-70B-ShiningValiant2-exl2-4b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "titan087/Llama3-70B-ShiningValiant2-exl2-4b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/titan087/Llama3-70B-ShiningValiant2-exl2-4b

SGLang

How to use titan087/Llama3-70B-ShiningValiant2-exl2-4b 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 "titan087/Llama3-70B-ShiningValiant2-exl2-4b" \
    --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": "titan087/Llama3-70B-ShiningValiant2-exl2-4b",
		"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 "titan087/Llama3-70B-ShiningValiant2-exl2-4b" \
        --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": "titan087/Llama3-70B-ShiningValiant2-exl2-4b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use titan087/Llama3-70B-ShiningValiant2-exl2-4b with Docker Model Runner:
```
docker model run hf.co/titan087/Llama3-70B-ShiningValiant2-exl2-4b
```

Exllama2 4bit Quantization

Shining Valiant 2 is a chat model built on Llama 3 70b, finetuned on our data for friendship, insight, knowledge and enthusiasm.

Finetuned on meta-llama/Meta-Llama-3-70B-Instruct for best available general performance
Trained on our data, focused on science, engineering, technical knowledge, and structured reasoning

Version

This is the 2024-04-20 release of Shining Valiant 2 for Llama 3 70b.

We're working on more Llama 3 releases to come, including Shining Valiant and our Build Tools set of models. We're excited to bring these to everyone soon!

Prompting Guide

Shining Valiant 2 uses the Llama 3 Instruct prompt format:

<|begin_of_text|><|start_header_id|>system<|end_header_id|>{{ system_prompt }}<|eot_id|><|start_header_id|>user<|end_header_id|>{{ user_msg_1 }}<|eot_id|><|start_header_id|>assistant<|end_header_id|>{{ model_answer_1 }}<|eot_id|>

Example input:

The Model

Shining Valiant 2 is built on top of Llama 3 70b Instruct, the highest performance open-source model currently available.

Our private data adds specialist knowledge and Shining Valiant's personality: she's friendly, enthusiastic, insightful, knowledgeable, and loves to learn!

Shining Valiant 2 is created by Valiant Labs.

Check out our HuggingFace page to see all of our models!

We care about open source. For everyone to use.

We encourage others to finetune further from our models.

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