Sentence Similarity
sentence-transformers
Safetensors
multilingual
neomme
multimodal
document-retrieval
dense-retrieval
Instructions to use Hcompany/NeoMME-800M-Retriever-ST-dense with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Hcompany/NeoMME-800M-Retriever-ST-dense with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Hcompany/NeoMME-800M-Retriever-ST-dense") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from Hcompany/NeoMME-800M-Retriever-ST-dense: direct link, hf CLI and curl.
- Browser
- Download file 515 Bytes
-
https://huggingface.co/Hcompany/NeoMME-800M-Retriever-ST-dense/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://Hcompany/NeoMME-800M-Retriever-ST-dense/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Hcompany/NeoMME-800M-Retriever-ST-dense/resolve/main/tokenizer_config.json
515 Bytes
| { | |
| "backend": "tokenizers", | |
| "clean_up_tokenization_spaces": false, | |
| "document_token": "<doc>", | |
| "eos_token": "<eos>", | |
| "extra_special_tokens": [], | |
| "image_token": "<img>", | |
| "mask_token": "<mask>", | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 16384, | |
| "pad_token": "<pad>", | |
| "processor_class": "NeoMMEProcessor", | |
| "query_token": "<query>", | |
| "row_token": "<row>", | |
| "tokenizer_class": "TokenizersBackend", | |
| "truncation_side": "right", | |
| "unk_token": "<unk>" | |
| } | |