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BASF-AI
/
ChEmbed-plug

Feature Extraction
Transformers
Safetensors
nomic_bert
custom_code
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use BASF-AI/ChEmbed-plug with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use BASF-AI/ChEmbed-plug with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="BASF-AI/ChEmbed-plug", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("BASF-AI/ChEmbed-plug", trust_remote_code=True)
    model = AutoModel.from_pretrained("BASF-AI/ChEmbed-plug", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
ChEmbed-plug
Ctrl+K
Ctrl+K
  • 1 contributor
History: 7 commits
hsila's picture
hsila
Add extra file 1_Pooling/config.json
e694513 verified about 1 year ago
  • 1_Pooling
    Add extra file 1_Pooling/config.json about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    5.17 kB
    Upload model about 1 year ago
  • config.json
    1.56 kB
    Upload model about 1 year ago
  • configuration_hf_nomic_bert.py
    1.96 kB
    Add configuration_hf_nomic_bert.py about 1 year ago
  • model.safetensors
    547 MB
    xet
    Upload model about 1 year ago
  • modeling_hf_nomic_bert.py
    85.5 kB
    Add modeling_hf_nomic_bert.py about 1 year ago
  • modules.json
    349 Bytes
    Add extra file modules.json about 1 year ago
  • sentence_bert_config.json
    54 Bytes
    Add extra file sentence_bert_config.json about 1 year ago