Instructions to use OpenGenerativeAI/testModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGenerativeAI/testModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="OpenGenerativeAI/testModel")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("OpenGenerativeAI/testModel") model = AutoModelForCausalLM.from_pretrained("OpenGenerativeAI/testModel") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use OpenGenerativeAI/testModel with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OpenGenerativeAI/testModel" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenGenerativeAI/testModel", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/OpenGenerativeAI/testModel
- SGLang
How to use OpenGenerativeAI/testModel 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 "OpenGenerativeAI/testModel" \ --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": "OpenGenerativeAI/testModel", "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 "OpenGenerativeAI/testModel" \ --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": "OpenGenerativeAI/testModel", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use OpenGenerativeAI/testModel with Docker Model Runner:
docker model run hf.co/OpenGenerativeAI/testModel
| license: apache-2.0 | |
| language: | |
| - en | |
| #### This Model | |
| This is an intermediate checkpoint with 480K steps and 1007B tokens. | |
| #### How to use | |
| You will need the transformers>=4.31 | |
| ```python | |
| from transformers import AutoTokenizer | |
| import transformers | |
| import torch | |
| model = "OpenGenerativeAI/testModel" | |
| tokenizer = AutoTokenizer.from_pretrained(model) | |
| pipeline = transformers.pipeline( | |
| "text-generation", | |
| model=model, | |
| torch_dtype=torch.float16, | |
| device_map="auto", | |
| ) | |
| sequences = pipeline( | |
| 'The TinyLlama project aims to pretrain a 1.1B Llama model on 3 trillion tokens. With some proper optimization, we can achieve this within a span of "just" 90 days using 16 A100-40G GPUs ๐๐. The training has started on 2023-09-01.', | |
| do_sample=True, | |
| top_k=10, | |
| num_return_sequences=1, | |
| repetition_penalty=1.5, | |
| eos_token_id=tokenizer.eos_token_id, | |
| max_length=500, | |
| ) | |
| for seq in sequences: | |
| print(f"Result: {seq['generated_text']}") | |
| ``` |