Instructions to use pfnet/plamo-13b-instruct-nc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pfnet/plamo-13b-instruct-nc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="pfnet/plamo-13b-instruct-nc", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("pfnet/plamo-13b-instruct-nc", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use pfnet/plamo-13b-instruct-nc with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "pfnet/plamo-13b-instruct-nc" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "pfnet/plamo-13b-instruct-nc", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/pfnet/plamo-13b-instruct-nc
- SGLang
How to use pfnet/plamo-13b-instruct-nc 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 "pfnet/plamo-13b-instruct-nc" \ --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": "pfnet/plamo-13b-instruct-nc", "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 "pfnet/plamo-13b-instruct-nc" \ --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": "pfnet/plamo-13b-instruct-nc", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use pfnet/plamo-13b-instruct-nc with Docker Model Runner:
docker model run hf.co/pfnet/plamo-13b-instruct-nc
Commit History
8 days ago
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Update README.md (#3)
- Update README.md (4db8fd211bd7ae1b7b8e55eece41e79361890bbe) Co-authored-by: ota42y <ota42y@users.noreply.huggingface.co>ace21b5
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Add "chat_template" to tokenizer_config.json (#2)
Verified signature- Add "chat_template" to tokenizer_config.json (8437c8db8865f6b13b8e73a8ab68b8cacec1bd13) - Add assistant role (5d1946bb50efeae43d51003a43f40ac313625889) - Update tokenizer_config.json (115ea9a671fa2fa617691d065563e22ef71ae160) - Add assistant content to prompt (4dc99c7f552085f8c0baf07c6ab9245956f1b383) Co-authored-by: Shunta Saito <mitmul@users.noreply.huggingface.co>3f2a13e
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Change the value of add_eos_token to false (#1)
Verified signature- Change the value of add_eos_token to false (f534ac57c8982060e82bfbd0d99e3eee9bef8be1) Co-authored-by: Shunta Saito <mitmul@users.noreply.huggingface.co>266167a
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