Instructions to use argilla/notus-7b-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use argilla/notus-7b-v1 with Transformers:

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

pipe = pipeline("text-generation", model="argilla/notus-7b-v1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("argilla/notus-7b-v1")
model = AutoModelForCausalLM.from_pretrained("argilla/notus-7b-v1", device_map="auto")
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 argilla/notus-7b-v1 with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/argilla/notus-7b-v1

SGLang

How to use argilla/notus-7b-v1 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 "argilla/notus-7b-v1" \
    --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": "argilla/notus-7b-v1",
		"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 "argilla/notus-7b-v1" \
        --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": "argilla/notus-7b-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use argilla/notus-7b-v1 with Docker Model Runner:
```
docker model run hf.co/argilla/notus-7b-v1
```

corrected 'generate' demo code

by macadeliccc - opened Dec 1, 2023

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

-3

macadeliccc

Dec 1, 2023

changed 'prompt' to 'messages' to correct generation error.

added explicit device assertion to alleviate this error:
RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! (when checking argument for argument index in method wrapper_CUDA__index_select)

added eos token to prevent open ended generation
added a print statement so the user can read the generated content.

corrected 'generate' demo code2dea99e7

alvarobartt

Dec 2, 2023

Hi Tim, thanks for this PR! LGTM, but can we keep the device_map="auto" instead? 🤗

macadeliccc

Dec 2, 2023

Absolutely, it’s your project. I just had some issues with it but if other people need to they can just change the device on their own like I did.

alvarobartt

Dec 2, 2023

No worries at all, I’ll try to reproduce to see if I also have the same issue, thanks for reporting! Coming back to this on Monday, but thanks a lot for the comments and the PR 🫶🏻

macadeliccc

Dec 2, 2023

sounds good, have a nice weekend!

alvarobartt

Dec 4, 2023

Hi @macadeliccc , I've reproduced in a Google Colab, feel free to use the code and output from there 🤗 Also to add the output so that users know what's the expected output

See https://colab.research.google.com/drive/1wHgYZQUtomhqFZHfTVFaDMbR8g8MjjkA?usp=sharing, thanks for the issue!

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