Instructions to use Intel/neural-chat-7b-v3-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Intel/neural-chat-7b-v3-3 with Transformers:

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

pipe = pipeline("text-generation", model="Intel/neural-chat-7b-v3-3")
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-v3-3")
model = AutoModelForCausalLM.from_pretrained("Intel/neural-chat-7b-v3-3")
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 Intel/neural-chat-7b-v3-3 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-v3-3"
# 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-v3-3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Intel/neural-chat-7b-v3-3

SGLang

How to use Intel/neural-chat-7b-v3-3 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-v3-3" \
    --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-v3-3",
		"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-v3-3" \
        --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-v3-3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Intel/neural-chat-7b-v3-3 with Docker Model Runner:
```
docker model run hf.co/Intel/neural-chat-7b-v3-3
```

neural-chat-7b-v3-3

Commit History

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Commit History

Adding `safetensors` variant of this model (#14) 7506dfc verified

add chat template. 52d98fd

Adding Evaluation Results (#10) bdd31cf verified

Update README.md 59b1af1 verified

Update README.md cdce282 verified

Update README.md a20ffb5 verified

Update README.md bd11ee4 verified

Update README.md (#7) 7b86016 verified

Minor updates to README (#1) 558b0ef

update doc. 1b2b346

add model fac83ab

update doc. e53e64d

update doc. de75fa7

initial commit 9b9acb6

Adding `safetensors` variant of this model (#14)

7506dfc
verified

add chat template.

52d98fd

Adding Evaluation Results (#10)

bdd31cf
verified

Update README.md

59b1af1
verified

Update README.md

cdce282
verified

Update README.md

a20ffb5
verified

Update README.md

bd11ee4
verified

Update README.md (#7)

7b86016
verified

Minor updates to README (#1)

558b0ef

update doc.

1b2b346

add model

fac83ab

update doc.

e53e64d

update doc.

de75fa7

initial commit

9b9acb6