Model reference · open weights
distilbert-nli-mean-tokens is an open-weight embedding model from sentence-transformers, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
⚠️ This model is deprecated. Please don't use it as it produces sentence embeddings of low quality. You can find recommended sentence embedding models here: SBERT.net - Pretrained Models sentence-transformers/distilbert-base-nli-mean-tokens This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search. Usage (Sentence-Transformers) Using this model becomes easy when you have sentence-transformers installed: Then you can use the model like this: Usage (HuggingFace Transformers) Without sentence-transformers, you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings. Full Model Architecture Citing & Authors This model was trained by sentence-transformers. If you find this model helpful, feel free to cite our publication Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks:
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | sentence-transformers |
|---|---|
| Type | Embedding models |
| Parameters (lead) | 66M |
| Context | 512 tokens |
| Variants | 1 |
| Runs with | sentence-transformers |
| Released | 2022-03-02 |
| Popularity | 111k downloads / month |
| Likes | 13 |
| Licence | Open weights |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| distilbert-base-nli-mean-tokens | 66M | BF16 | ~0.2 GB | ✓ | Weights ↗ |
Using it via the API
Once AxForge deploys distilbert-nli-mean-tokens for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (distilbert-nli-mean-tokens 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":"distilbert-nli-mean-tokens","input":"text to embed"}'
Licence
Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗
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