Text Classification
Transformers
PyTorch
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use JOSEDURANisc/practicaNLP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JOSEDURANisc/practicaNLP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JOSEDURANisc/practicaNLP")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JOSEDURANisc/practicaNLP") model = AutoModelForSequenceClassification.from_pretrained("JOSEDURANisc/practicaNLP") - 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:e44bf5d99ccfe2aba6d7d79a6d24b35a1271dd7fd08438283f3d019a7ef74aaf
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size 328492280
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