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friedrichor
/
Unite-Instruct-Qwen2-VL-2B

Feature Extraction
sentence-transformers
Safetensors
Transformers
English
qwen2_vl
sentence-similarity
multimodal
retrieval
image-text-to-text
video-text-to-text
any-to-any
Model card Files Files and versions
xet
Community

Instructions to use friedrichor/Unite-Instruct-Qwen2-VL-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use friedrichor/Unite-Instruct-Qwen2-VL-2B with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("friedrichor/Unite-Instruct-Qwen2-VL-2B")
    
    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 friedrichor/Unite-Instruct-Qwen2-VL-2B with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="friedrichor/Unite-Instruct-Qwen2-VL-2B")
    # Load model directly
    from transformers import AutoProcessor, UniteQwen2VL
    
    processor = AutoProcessor.from_pretrained("friedrichor/Unite-Instruct-Qwen2-VL-2B")
    model = UniteQwen2VL.from_pretrained("friedrichor/Unite-Instruct-Qwen2-VL-2B")
  • Notebooks
  • Google Colab
  • Kaggle
Unite-Instruct-Qwen2-VL-2B
4.43 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 9 commits
friedrichor's picture
friedrichor
Upload Training Logs
59501f2 verified 12 months ago
  • adapter_info
    Upload Training Logs 12 months ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    7.01 kB
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  • added_tokens.json
    392 Bytes
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  • chat_template.json
    1.05 kB
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  • config.json
    1.12 kB
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  • generation_config.json
    244 Bytes
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  • merges.txt
    1.67 MB
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  • model.safetensors
    4.42 GB
    xet
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  • preprocessor_config.json
    347 Bytes
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  • special_tokens_map.json
    613 Bytes
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  • tokenizer.json
    7.03 MB
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  • tokenizer_config.json
    4.19 kB
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  • vocab.json
    2.78 MB
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