Sentence Similarity
Transformers
PyTorch
Safetensors
xlm-roberta
feature-extraction
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use deepfile/embedder-100p with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepfile/embedder-100p with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("deepfile/embedder-100p") model = AutoModel.from_pretrained("deepfile/embedder-100p") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 40b7defc2d2330fe6ff37e677d74627184e361a8399444c841906a2b432adeb7
- Size of remote file:
- 1.11 GB
- SHA256:
- 9529752223e4bd6bfe717f5b0d4e0a9a0a7751ac541402b2d3a643fcdb52262d
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