Instructions to use geekfeed/gpt2_ja with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use geekfeed/gpt2_ja with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="geekfeed/gpt2_ja")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("geekfeed/gpt2_ja") model = AutoModel.from_pretrained("geekfeed/gpt2_ja", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from geekfeed/gpt2_ja: direct link, hf CLI and curl.
- Browser
- Download file 454 MB
-
https://huggingface.co/geekfeed/gpt2_ja/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://geekfeed/gpt2_ja/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/geekfeed/gpt2_ja/resolve/main/pytorch_model.bin
454 MB
- Xet hash:
- c0f3570b8cd352b8369b27c6ef77c4b49866a59af03e17721e7166b36b478684
- Size of remote file:
- 454 MB
- SHA256:
- f8051863ce61b5540f3b3dd99447906edc4d4be2dafedc647ffc71c9bcacb5aa
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