Text Generation
Transformers
PyTorch
TensorFlow
JAX
LiteRT
Rust
English
gpt2
exbert
text-generation-inference
Instructions to use baffo32/gpt2-ptmap with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use baffo32/gpt2-ptmap with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="baffo32/gpt2-ptmap")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("baffo32/gpt2-ptmap") model = AutoModelForCausalLM.from_pretrained("baffo32/gpt2-ptmap", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use baffo32/gpt2-ptmap with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "baffo32/gpt2-ptmap" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "baffo32/gpt2-ptmap", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/baffo32/gpt2-ptmap
- SGLang
How to use baffo32/gpt2-ptmap 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 "baffo32/gpt2-ptmap" \ --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": "baffo32/gpt2-ptmap", "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 "baffo32/gpt2-ptmap" \ --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": "baffo32/gpt2-ptmap", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use baffo32/gpt2-ptmap with Docker Model Runner:
docker model run hf.co/baffo32/gpt2-ptmap
Download flax_model.msgpack from baffo32/gpt2-ptmap: direct link, hf CLI and curl.
- Browser
- Download file 498 MB
-
https://huggingface.co/baffo32/gpt2-ptmap/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://baffo32/gpt2-ptmap/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/baffo32/gpt2-ptmap/resolve/main/flax_model.msgpack
498 MB
- Xet hash:
- 120fa10c9a116a074e005da769ce67c62b6e524424e630d068e00c23baa21d8d
- Size of remote file:
- 498 MB
- SHA256:
- 192e8257ae9e8f796f764630f4a488a6a16d1461762d62b49ef7405df951a283
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