Text Generation
Transformers
Safetensors
English
gemma
function calling
on-device language model
android
conversational
text-generation-inference
Instructions to use NexaAI/Octopus-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NexaAI/Octopus-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="NexaAI/Octopus-v2") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("NexaAI/Octopus-v2") model = AutoModelForCausalLM.from_pretrained("NexaAI/Octopus-v2") 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 NexaAI/Octopus-v2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "NexaAI/Octopus-v2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "NexaAI/Octopus-v2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/NexaAI/Octopus-v2
- SGLang
How to use NexaAI/Octopus-v2 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 "NexaAI/Octopus-v2" \ --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": "NexaAI/Octopus-v2", "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 "NexaAI/Octopus-v2" \ --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": "NexaAI/Octopus-v2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use NexaAI/Octopus-v2 with Docker Model Runner:
docker model run hf.co/NexaAI/Octopus-v2
Zack Zhiyuan Li commited on
Commit ·
9be03ce
1
Parent(s): 537313f
add video demo
Browse files
README.md
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- <a href="https://www.nexa4ai.com/" target="_blank">Nexa AI Product</a>
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- <a href="https://arxiv.org/abs/2404.01744" target="_blank">ArXiv</a>
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## Introducing Octopus-V2-2B
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- <a href="https://www.nexa4ai.com/" target="_blank">Nexa AI Product</a>
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- <a href="https://arxiv.org/abs/2404.01744" target="_blank">ArXiv</a>
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- <a href="https://www.youtube.com/watch?v=jhM0D0OObOw&ab_channel=NexaAI" target="_blank">Video Demo</a>
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<iframe width="560" height="315" src="https://www.youtube.com/embed/jhM0D0OObOw?autoplay=1&mute=1" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen style="display: block; margin: auto;"></iframe>
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## Introducing Octopus-V2-2B
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