Instructions to use hf-tiny-model-private/tiny-random-GPTNeoXJapaneseModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-GPTNeoXJapaneseModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-GPTNeoXJapaneseModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-GPTNeoXJapaneseModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-GPTNeoXJapaneseModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45f576904d13c1861d68144693443c63e79e4a94bbcfd65d5d2a2d98e708b063
- Size of remote file:
- 4.35 MB
- SHA256:
- acfbe9783e149dcf215d1909dc2909ff681090e76f52a0dac71429aacf8dfd60
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.