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ethicalabs
/
Echo-DSRN-v0.1.4-Embed-Intent-CLF

Text Classification
Transformers
Safetensors
multilingual
echo
echo-dsrn
intent-classification
massive
recurrent-neural-network
sklearn-initialized
custom_code
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use ethicalabs/Echo-DSRN-v0.1.4-Embed-Intent-CLF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ethicalabs/Echo-DSRN-v0.1.4-Embed-Intent-CLF with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="ethicalabs/Echo-DSRN-v0.1.4-Embed-Intent-CLF", trust_remote_code=True)
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoModelForSequenceClassification
    model = AutoModelForSequenceClassification.from_pretrained("ethicalabs/Echo-DSRN-v0.1.4-Embed-Intent-CLF", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Echo-DSRN-v0.1.4-Embed-Intent-CLF
397 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 43 commits
mrs83's picture
mrs83
docs: note that a right-padded training version is planned
ae2efe1 verified about 2 months ago
  • scripts
    Upload folder using huggingface_hub 3 months ago
  • .gitattributes
    1.52 kB
    initial commit 3 months ago
  • README.md
    39.8 kB
    docs: note that a right-padded training version is planned about 2 months ago
  • chat_template.jinja
    2.43 kB
    Upload folder using huggingface_hub about 2 months ago
  • config.json
    4.46 kB
    config: route AutoModel to EchoModelForPooling for vLLM weight mapping about 2 months ago
  • configuration_echo.py
    4.38 kB
    Upload folder using huggingface_hub about 2 months ago
  • model.safetensors
    394 MB
    xet
    Upload folder using huggingface_hub 3 months ago
  • modeling_echo.py
    79.8 kB
    Upload folder using huggingface_hub about 2 months ago
  • modeling_embedding.py
    8.99 kB
    Upload folder using huggingface_hub about 2 months ago
  • tokenizer.json
    3.62 MB
    Upload folder using huggingface_hub 3 months ago
  • tokenizer_config.json
    751 Bytes
    config: restore left padding — published MTEB benchmarks were measured with left padding; card parity is the priority (right-padded training lands in the next model version) about 2 months ago
  • triton_scan.py
    16.5 kB
    Upload folder using huggingface_hub 3 months ago
  • utils.py
    1.91 kB
    Upload folder using huggingface_hub about 2 months ago