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McGill-NLP
/
LLM2Vec-Gen-Qwen25-3B

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
Model card Files Files and versions
xet
Community

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:

    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("McGill-NLP/LLM2Vec-Gen-Qwen25-3B", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
LLM2Vec-Gen-Qwen25-3B
654 MB
Ctrl+K
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  • 1 contributor
History: 25 commits
parishadbehnam's picture
parishadbehnam
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  • .gitattributes
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  • README.md
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  • added_tokens.json
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  • alignment_mlp
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  • chat_template.jinja
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  • config.json
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  • encoder_decoder_config.json
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  • merges.txt
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  • reconstruction_mlp
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  • run_config.yml
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  • special_tokens_map.json
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  • tokenizer.json
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  • tokenizer_config.json
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  • vocab.json
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