Sentence Similarity
Transformers
Safetensors
text-embedding
embeddings
information-retrieval
beir
text-classification
language-model
text-clustering
text-semantic-similarity
text-evaluation
text-reranking
feature-extraction
Sentence Similarity
natural_questions
ms_marco
fever
hotpot_qa
mteb
advbenchir
bright
Instructions to use McGill-NLP/LLM2Vec-Gen-Qwen25-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use McGill-NLP/LLM2Vec-Gen-Qwen25-3B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("McGill-NLP/LLM2Vec-Gen-Qwen25-3B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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library_name: transformers
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license: mit
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pipeline_tag: sentence-similarity
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base_model: Qwen/
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tags:
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- text-embedding
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- embeddings
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library_name: transformers
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license: mit
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pipeline_tag: sentence-similarity
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base_model: Qwen/Qwen2.5-3B-Instruct
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tags:
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- text-embedding
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- embeddings
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