Feature Extraction
sentence-transformers
PyTorch
Safetensors
Transformers
English
distilbert
fill-mask
learned sparse
opensearch
retrieval
passage-retrieval
document-expansion
bag-of-words
sparse-encoder
sparse
asymmetric
inference-free
splade
text-embeddings-inference
Instructions to use opensearch-project/opensearch-neural-sparse-encoding-doc-v2-distill with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use opensearch-project/opensearch-neural-sparse-encoding-doc-v2-distill with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("opensearch-project/opensearch-neural-sparse-encoding-doc-v2-distill") 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] - Transformers
How to use opensearch-project/opensearch-neural-sparse-encoding-doc-v2-distill with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="opensearch-project/opensearch-neural-sparse-encoding-doc-v2-distill")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("opensearch-project/opensearch-neural-sparse-encoding-doc-v2-distill") model = AutoModelForMaskedLM.from_pretrained("opensearch-project/opensearch-neural-sparse-encoding-doc-v2-distill", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from opensearch-project/opensearch-neural-sparse-encoding-doc-v2-distill: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/opensearch-project/opensearch-neural-sparse-encoding-doc-v2-distill/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://opensearch-project/opensearch-neural-sparse-encoding-doc-v2-distill/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/opensearch-project/opensearch-neural-sparse-encoding-doc-v2-distill/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- d8c538992121568b7b7bb5d55eeab951c81c518862cf1f6b901b70de0a6af717
- Size of remote file:
- 268 MB
- SHA256:
- b0d73c64580e010c4e28c864efa7e7192b85eaee6bbceb8c24680885a75704de
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