Instructions to use Vydiant/mesh-pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vydiant/mesh-pipeline with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Vydiant/mesh-pipeline")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Vydiant/mesh-pipeline") model = AutoModel.from_pretrained("Vydiant/mesh-pipeline", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c00bf5f764da90c5b77c00c2982729e11c22df9ae53fd49def88f81f7e6bee08
- Size of remote file:
- 433 MB
- SHA256:
- a73fcac8e061a9a048b9f2ef4d49c4cdd8540f4b0123e20918a275a8007121e7
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