Text Classification
Transformers
PyTorch
TensorBoard
mpnet
Generated from Trainer
text-embeddings-inference
Instructions to use ilaria-oneofftech/ikitracs_conditional with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ilaria-oneofftech/ikitracs_conditional with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ilaria-oneofftech/ikitracs_conditional")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ilaria-oneofftech/ikitracs_conditional") model = AutoModelForSequenceClassification.from_pretrained("ilaria-oneofftech/ikitracs_conditional", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:dc976dfe3018a05d6f5d6be3da75cb978e9871a4ff28c56b1ffc7fa2ee9d5eb3
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size 437979400
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