Instructions to use Nexusflow/NexusRaven-V2-13B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Nexusflow/NexusRaven-V2-13B with Transformers:

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

pipe = pipeline("text-generation", model="Nexusflow/NexusRaven-V2-13B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Nexusflow/NexusRaven-V2-13B")
model = AutoModelForCausalLM.from_pretrained("Nexusflow/NexusRaven-V2-13B")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Nexusflow/NexusRaven-V2-13B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Nexusflow/NexusRaven-V2-13B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Nexusflow/NexusRaven-V2-13B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Nexusflow/NexusRaven-V2-13B

SGLang

How to use Nexusflow/NexusRaven-V2-13B 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 "Nexusflow/NexusRaven-V2-13B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Nexusflow/NexusRaven-V2-13B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "Nexusflow/NexusRaven-V2-13B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Nexusflow/NexusRaven-V2-13B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Nexusflow/NexusRaven-V2-13B with Docker Model Runner:
```
docker model run hf.co/Nexusflow/NexusRaven-V2-13B
```

Train Data?

by unaidedelf87777 - opened Dec 5, 2023

Discussion

unaidedelf87777

Dec 5, 2023

Is the train data public, and if so where can we find it?

If the data isn’t currently public, will it be released? would be awesome if it could be!

venkat-srinivasan-nvidia

Nexusflow org Dec 5, 2023

Hi Nathan! Thank you for your interest! This is on our roadmap so please stay tuned!

venkat-srinivasan-nvidia changed discussion status to closed Dec 5, 2023

unaidedelf87777

Dec 5, 2023

Hi Nathan! Thank you for your interest! This is on our roadmap so please stay tuned!

any ETA? I am planning on a run of finetunes soon, I’d love to put it in, but i plan on training in ~10 days.

ehartford

Dec 5, 2023

Data please? 🤤

unaidedelf87777

Dec 6, 2023

Data please? 🤤

What Eric said!

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