Instructions to use valhalla/awesome-model_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use valhalla/awesome-model_v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="valhalla/awesome-model_v3", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("valhalla/awesome-model_v3", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 257d928ac2d9525529102e41fdab5cde2cba485b51c57f768c000a45cdd6fc31
- Size of remote file:
- 2.24 kB
- SHA256:
- b0ba636ff7e5e8603c4007c9ed8f6584474e99d16db47e5d4e5eb55643cf55d3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.