Text Generation
Transformers
PyTorch
TensorFlow
JAX
LiteRT
Rust
Core ML
Safetensors
English
gpt2
exbert
Eval Results (legacy)
text-generation-inference
Instructions to use jiajiahong2134/DLhw2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jiajiahong2134/DLhw2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="jiajiahong2134/DLhw2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("jiajiahong2134/DLhw2") model = AutoModelForCausalLM.from_pretrained("jiajiahong2134/DLhw2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use jiajiahong2134/DLhw2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jiajiahong2134/DLhw2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jiajiahong2134/DLhw2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/jiajiahong2134/DLhw2
- SGLang
How to use jiajiahong2134/DLhw2 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 "jiajiahong2134/DLhw2" \ --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": "jiajiahong2134/DLhw2", "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 "jiajiahong2134/DLhw2" \ --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": "jiajiahong2134/DLhw2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use jiajiahong2134/DLhw2 with Docker Model Runner:
docker model run hf.co/jiajiahong2134/DLhw2
Download flax_model.msgpack from jiajiahong2134/DLhw2: direct link, hf CLI and curl.
- Browser
- Download file 328 MB
-
https://huggingface.co/jiajiahong2134/DLhw2/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://jiajiahong2134/DLhw2/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/jiajiahong2134/DLhw2/resolve/main/flax_model.msgpack
328 MB
- Xet hash:
- ab6aea69512ae250f71886c4dc196c3cb3abf90a2e26f039ce536691d693dcee
- Size of remote file:
- 328 MB
- SHA256:
- b3b7fcf75195b7c4d8a73bf26f8b1344f2186bdcd3715f04e0c04ae76d5931be
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