Model reference · open weights
msmarco-roberta-ance-firstp is an open-weight embedding model from sentence-transformers. 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 | sentence-transformers |
|---|---|
| Type | Embedding models |
| Task | Embeddings |
| Parameters (lead) | 125M |
| Context | 514 tokens |
| Runs with | sentence-transformers |
| Released | 2022-03-02 |
| Popularity | 1k downloads / month |
| Licence | Open weights |
About
This is a port of the ANCE FirstP Model to 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.
Using this model becomes easy when you have sentence-transformers installed:
pip install -U sentence-transformers
Then you can use the model like this:
from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]
model = SentenceTransformer('sentence-transformers/msmarco-roberta-base-ance-firstp')
embeddings = model.encode(sentences)
print(embeddings)
SentenceTransformer(
(0): Transformer({'max_seq_length': 512, 'do_lower_case': True}) with Transformer model: RobertaModel
(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
(2): Dense({'in_features': 768, 'out_features': 768, 'bias': True, 'activation_function': 'torch.nn.modules.linear.Identity'})
(3): LayerNorm(
(norm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
)
)
Have a look at: ANCE Model
From the published model card. Full card on the HuggingFace links in the sidebar.
Using it via the API
Once AxForge deploys msmarco-roberta-ance-firstp for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (msmarco-roberta-ance-firstp 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":"msmarco-roberta-ance-firstp","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.