Instructions to use openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf") model = AutoModelForCausalLM.from_pretrained("openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf
- SGLang
How to use openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf 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 "openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf" \ --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": "openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf", "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 "openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf" \ --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": "openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf with Docker Model Runner:
docker model run hf.co/openthaigpt/openthaigpt-1.0.0-beta-13b-chat-hf
| { | |
| "</s>": 2, | |
| "<CLS>": 41070, | |
| "<EOD>": 41072, | |
| "<MASK>": 41073, | |
| "<PAD>": 41074, | |
| "<SEP>": 41071, | |
| "<s>": 1, | |
| "<unk>": 0, | |
| "<unused1>": 41075, | |
| "<unused2>": 41076, | |
| "<unused3>": 41077, | |
| "<unused4>": 41078, | |
| "<unused5>": 41079, | |
| "<unused6>": 41080, | |
| "<unused7>": 41081, | |
| "<unused8>": 41081, | |
| "<unused9>": 41082, | |
| "<unused10>": 41082, | |
| "<unused11>": 41083, | |
| "<unused12>": 41084, | |
| "<unused13>": 41085, | |
| "<unused14>": 41086, | |
| "<unused15>": 41087 | |
| } | |