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MoLeMo-Lab
/
mojev

Text Classification
Transformers
ONNX
Safetensors
mojev-scorer
feature-extraction
calibration
structured-output
multiple-choice
preference-learning
multimodal
mojev
custom_code
Eval Results (legacy)
Model card Files Files and versions
xet

Instructions to use MoLeMo-Lab/mojev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use MoLeMo-Lab/mojev with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="MoLeMo-Lab/mojev", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("MoLeMo-Lab/mojev", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
mojev
2.33 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
di-zhang-fdu's picture
di-zhang-fdu
Publish MoJev
0c8695b about 13 hours ago
  • browser
    Publish MoJev about 13 hours ago
  • .gitattributes
    1.57 kB
    Publish MoJev about 13 hours ago
  • README.md
    6.72 kB
    Publish MoJev about 13 hours ago
  • chat_template.jinja
    7.76 kB
    Publish MoJev about 13 hours ago
  • config.json
    5.94 kB
    Publish MoJev about 13 hours ago
  • model.safetensors
    1.71 GB
    xet
    Publish MoJev about 13 hours ago
  • modeling.py
    13.4 kB
    Publish MoJev about 13 hours ago
  • preprocessor_config.json
    334 Bytes
    Publish MoJev about 13 hours ago
  • schema.py
    7.07 kB
    Publish MoJev about 13 hours ago
  • tokenizer.json
    20 MB
    xet
    Publish MoJev about 13 hours ago
  • tokenizer_config.json
    1.12 kB
    Publish MoJev about 13 hours ago
  • video_preprocessor_config.json
    332 Bytes
    Publish MoJev about 13 hours ago