huggingface / huggingface/sentence-transformers

Workaround mirror for slow model downloading

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Dominant language
Python
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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

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