Instructions to use Wenwu190200201/spaiss6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wenwu190200201/spaiss6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Wenwu190200201/spaiss6")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Wenwu190200201/spaiss6") model = AutoModelForCausalLM.from_pretrained("Wenwu190200201/spaiss6") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Wenwu190200201/spaiss6 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Wenwu190200201/spaiss6" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Wenwu190200201/spaiss6", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Wenwu190200201/spaiss6
- SGLang
How to use Wenwu190200201/spaiss6 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 "Wenwu190200201/spaiss6" \ --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": "Wenwu190200201/spaiss6", "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 "Wenwu190200201/spaiss6" \ --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": "Wenwu190200201/spaiss6", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Wenwu190200201/spaiss6 with Docker Model Runner:
docker model run hf.co/Wenwu190200201/spaiss6
DataThai-1M-playground-improved
Playable tiny Thai-English toy model for pipeline testing.
This is not DataThai-1B. It is a ~1M parameter smoke/playground model trained on a tiny QA-style demo corpus.
Use it for:
- loading test
- generation test
- Hugging Face deploy test
- sharing a small runnable model artifact
Do not use it as a real language model benchmark.
Wenwu190200201/spaiss6
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