Feature Extraction
Transformers
Safetensors
qwen3_5_text
embeddings
retrieval
buddhist-studies
sanskrit
tibetan
classical-chinese
pali
Instructions to use buddhist-nlp/mitra-qwen35-embedder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use buddhist-nlp/mitra-qwen35-embedder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="buddhist-nlp/mitra-qwen35-embedder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("buddhist-nlp/mitra-qwen35-embedder") model = AutoModel.from_pretrained("buddhist-nlp/mitra-qwen35-embedder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac0265e7df111e3971990e5187e91dff1752d3b102a34e70fefeffc315e8704a
- Size of remote file:
- 15.9 GB
- SHA256:
- 4191d022f16dc835302d508932a9da5562f126d00f11bcca56e89528abf505a8
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