Instructions to use dani0f/model3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dani0f/model3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dani0f/model3")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dani0f/model3") model = AutoModel.from_pretrained("dani0f/model3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bae47693876cab2d0270248884eb217fae80fbc743ab4806db0565d8724f29f0
- Size of remote file:
- 253 MB
- SHA256:
- c035754992091ec6f78a56738cef1911fb16a493b0dd432b49802375bb263cd2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.