huggingface / huggingface/sentence-transformers
Workaround mirror for slow model downloading
- Dominant language
- Python
- Stars
- 19.1k
- Forks
- 2.9k
- Avg merge
- 1d 19h
- Merged PRs (30d)
- 61
Description
The `roberta-base-nli-stsb-mean-tokens` was taking 2+hrs to download for me so i uploaded it to huggingface/transformers generously open and 100x faster s3 bucket if this is useful for anyone.
Usage:
```
from sentence_transformers import SentenceTransformer
from sentence_transformers.models import RoBERTa
from sentence_transformers.models import Pooling
roberta = RoBERTa('pertschuk/0_RoBERTa')
pooling = Pooling(768)
model = SentenceTransformer(modules=[roberta, pooling])
```
Contributor guide
No contributing guide indexed for this repository
Research direction
No repository file, test, or entry point is named. Start by determining whether this workaround is intended as a project change or only a usage suggestion, then review the shown SentenceTransformer and RoBERTa usage with maintainers. Done requires an explicitly defined integration or documentation outcome.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- huggingface, python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100