Instructions to use VMware/vinilm-2021-from-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VMware/vinilm-2021-from-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="VMware/vinilm-2021-from-large")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("VMware/vinilm-2021-from-large") model = AutoModel.from_pretrained("VMware/vinilm-2021-from-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ac6756dbb550ff58707034d9ea2f9117fef7b008d49c591ced2fba95a5fca0d
- Size of remote file:
- 268 MB
- SHA256:
- 05c17d0c6ea4336628a31554b3603bac365df6fc4e0ba3e68facb491f5d3efc0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.