Sentence Similarity
sentence-transformers
Safetensors
PEFT
English
text-embeddings
retrieval
web-search
news
Instructions to use desearch/Desearch-Embedding-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use desearch/Desearch-Embedding-4B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("desearch/Desearch-Embedding-4B") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - PEFT
How to use desearch/Desearch-Embedding-4B with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from desearch/Desearch-Embedding-4B: direct link, hf CLI and curl.
- Browser
- Download file 402 Bytes
-
https://huggingface.co/desearch/Desearch-Embedding-4B/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://desearch/Desearch-Embedding-4B/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/desearch/Desearch-Embedding-4B/resolve/main/tokenizer_config.json
402 Bytes
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": null, | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|im_end|>", | |
| "errors": "replace", | |
| "is_local": false, | |
| "local_files_only": false, | |
| "model_max_length": 2048, | |
| "pad_token": "<|endoftext|>", | |
| "padding_side": "left", | |
| "split_special_tokens": false, | |
| "tokenizer_class": "Qwen2Tokenizer", | |
| "unk_token": null | |
| } | |