Text Generation
Transformers
PyTorch
TensorBoard
mixformer-sequential
Generated from Trainer
custom_code
Instructions to use simlamkr1/Llama2-simgpt2test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simlamkr1/Llama2-simgpt2test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="simlamkr1/Llama2-simgpt2test", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("simlamkr1/Llama2-simgpt2test", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use simlamkr1/Llama2-simgpt2test with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "simlamkr1/Llama2-simgpt2test" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "simlamkr1/Llama2-simgpt2test", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/simlamkr1/Llama2-simgpt2test
- SGLang
How to use simlamkr1/Llama2-simgpt2test 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 "simlamkr1/Llama2-simgpt2test" \ --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": "simlamkr1/Llama2-simgpt2test", "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 "simlamkr1/Llama2-simgpt2test" \ --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": "simlamkr1/Llama2-simgpt2test", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use simlamkr1/Llama2-simgpt2test with Docker Model Runner:
docker model run hf.co/simlamkr1/Llama2-simgpt2test
- Xet hash:
- cceac015e16707116eff8f7c76c468c03e6e9bf6033a15d8e693ddc2dd693dbf
- Size of remote file:
- 3.96 kB
- SHA256:
- af6cfbcd51ab3159df881af231a62745c278444d90055981f477d86d09c9d52e
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