Instructions to use Intel/neural-chat-7b-v3-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Intel/neural-chat-7b-v3-1 with Transformers:

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

pipe = pipeline("text-generation", model="Intel/neural-chat-7b-v3-1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Intel/neural-chat-7b-v3-1")
model = AutoModelForCausalLM.from_pretrained("Intel/neural-chat-7b-v3-1")
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 Settings

vLLM

How to use Intel/neural-chat-7b-v3-1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Intel/neural-chat-7b-v3-1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Intel/neural-chat-7b-v3-1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Intel/neural-chat-7b-v3-1

SGLang

How to use Intel/neural-chat-7b-v3-1 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 "Intel/neural-chat-7b-v3-1" \
    --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": "Intel/neural-chat-7b-v3-1",
		"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 "Intel/neural-chat-7b-v3-1" \
        --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": "Intel/neural-chat-7b-v3-1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Intel/neural-chat-7b-v3-1 with Docker Model Runner:
```
docker model run hf.co/Intel/neural-chat-7b-v3-1
```

What is the different between Intel/neural-chat-7b-v3-1 vs Intel/neural-chat-7b-v3?

by Ichsan2895 - opened Nov 15, 2023

Discussion

Ichsan2895

Nov 15, 2023

Hello, first of all. Thank you for releasing it with Apache 2.0 license.

But I am curious. What is the different (dataset/hyperparameter/steps/etc) between v3-1 and v3?

Delcos

Nov 27, 2023

There is an extra "1" in the title of the former. This is lacking in the other.

hair-is-long

Nov 28, 2023

There is an extra "1" in the title of the former. This is lacking in the other.

Ichsan2895

Nov 29, 2023

Wow, what an amazing answer. Really out of the box..

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