Instructions to use eooitom/phobertlong4096 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eooitom/phobertlong4096 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="eooitom/phobertlong4096")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("eooitom/phobertlong4096") model = AutoModel.from_pretrained("eooitom/phobertlong4096", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from eooitom/phobertlong4096: direct link, hf CLI and curl.
- Browser
- Download file 637 MB
-
https://huggingface.co/eooitom/phobertlong4096/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://eooitom/phobertlong4096/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/eooitom/phobertlong4096/resolve/main/pytorch_model.bin
637 MB
- Xet hash:
- 9df9f2b7dd45af6922c5bf70404c3a545ba36045499c403aab57c5968d31c58e
- Size of remote file:
- 637 MB
- SHA256:
- 296e02d5f6544ba97ffbb4590adba8ab65ab91d23a4328a032ce794677397bf0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.