Text Classification
Transformers
PyTorch
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use petermutwiri/NLP_Capstone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use petermutwiri/NLP_Capstone with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="petermutwiri/NLP_Capstone")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("petermutwiri/NLP_Capstone") model = AutoModelForSequenceClassification.from_pretrained("petermutwiri/NLP_Capstone", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
Verified signature- Adding `safetensors` variant of this model (52a1ff9679f7b59149b795c1d4ee087c261f9d0b) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>9fe6bb9
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