Instructions to use pythonformer/ascent_gen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pythonformer/ascent_gen with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="pythonformer/ascent_gen")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("pythonformer/ascent_gen") model = AutoModelForCausalLM.from_pretrained("pythonformer/ascent_gen") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use pythonformer/ascent_gen with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "pythonformer/ascent_gen" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "pythonformer/ascent_gen", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/pythonformer/ascent_gen
- SGLang
How to use pythonformer/ascent_gen 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 "pythonformer/ascent_gen" \ --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": "pythonformer/ascent_gen", "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 "pythonformer/ascent_gen" \ --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": "pythonformer/ascent_gen", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use pythonformer/ascent_gen with Docker Model Runner:
docker model run hf.co/pythonformer/ascent_gen
- Xet hash:
- 0af256b8ce2d4bd3892319cf010ce8bcd30a55f6413a3b51ee77c3a5f19fe2bd
- Size of remote file:
- 1.55 GB
- SHA256:
- 096ae8a6515f5f4fa7652229c26d37d55ef302f5d59a629923521fc1c8972327
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