Model reference · open weights
bert-tiny is an open-weight embedding model from lyeonii. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Released by | lyeonii |
|---|---|
| Type | Embedding models |
| Task | Embeddings |
| Context | 512 tokens |
| Runs with | transformers |
| Released | 2023-03-15 |
| Popularity | 538 downloads / month |
| Licence | Open weights |
About
This is the smallest version of 24 smaller BERT models (English only, uncased, trained with WordPiece masking) released by google-research/bert.
These BERT models was released as TensorFlow checkpoints, however, this is the converted version to PyTorch. More information can be found in google-research/bert or lyeoni/convert-tf-to-pytorch.
Here are the evaluation scores (F1/Accuracy) for the MPRC task.
| Model | MRPC |
|---|---|
| BERT-Tiny | 81.22/68.38 |
| BERT-Mini | 81.43/69.36 |
| BERT-Small | 81.41/70.34 |
| BERT-Medium | 83.33/73.53 |
| BERT-Base | 85.62/78.19 |
@article{turc2019,
title={Well-Read Students Learn Better: On the Importance of Pre-training Compact Models},
author={Turc, Iulia and Chang, Ming-Wei and Lee, Kenton and Toutanova, Kristina},
journal={arXiv preprint arXiv:1908.08962v2 },
year={2019}
}
From the published model card. Full card on the HuggingFace links in the sidebar.
Using it via the API
Once AxForge deploys bert-tiny for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (bert-tiny below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/embeddings \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"bert-tiny","input":"text to embed"}'
Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.