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drAbreu
/
soda-clip

Feature Extraction
Transformers
Safetensors
vision-text-dual-encoder
Generated from Trainer
Model card Files Files and versions
xet
Community

Instructions to use drAbreu/soda-clip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use drAbreu/soda-clip with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="drAbreu/soda-clip")
    # Load model directly
    from transformers import AutoProcessor, AutoModel
    
    processor = AutoProcessor.from_pretrained("drAbreu/soda-clip")
    model = AutoModel.from_pretrained("drAbreu/soda-clip", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
soda-clip
855 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 9 commits
drAbreu's picture
drAbreu
Model save
a9a06b9 verified about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    3.1 kB
    Model save about 2 years ago
  • config.json
    4.57 kB
    Training in progress, step 500 about 2 years ago
  • merges.txt
    456 kB
    Training in progress, step 500 about 2 years ago
  • model.safetensors
    852 MB
    xet
    Model save about 2 years ago
  • preprocessor_config.json
    521 Bytes
    Training in progress, step 500 about 2 years ago
  • special_tokens_map.json
    280 Bytes
    Training in progress, step 500 about 2 years ago
  • tokenizer.json
    2.11 MB
    Training in progress, step 500 about 2 years ago
  • tokenizer_config.json
    1.27 kB
    Training in progress, step 500 about 2 years ago
  • training_args.bin

    Detected Pickle imports (8)

    • "transformers.trainer_utils.HubStrategy",
    • "transformers.trainer_utils.IntervalStrategy",
    • "transformers.training_args.OptimizerNames",
    • "accelerate.utils.dataclasses.DistributedType",
    • "torch.device",
    • "transformers.trainer_utils.SchedulerType",
    • "accelerate.state.PartialState",
    • "transformers.training_args.TrainingArguments"

    How to fix it?

    4.66 kB
    xet
    Training in progress, step 500 about 2 years ago
  • vocab.json
    798 kB
    Training in progress, step 500 about 2 years ago