Instructions to use m-aliabbas1/roberta_en_med_merged_classes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m-aliabbas1/roberta_en_med_merged_classes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="m-aliabbas1/roberta_en_med_merged_classes")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("m-aliabbas1/roberta_en_med_merged_classes") model = AutoModelForSequenceClassification.from_pretrained("m-aliabbas1/roberta_en_med_merged_classes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1800, checkpoint
Browse files
last-checkpoint/model.safetensors
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last-checkpoint/optimizer.pt
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last-checkpoint/rng_state.pth
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last-checkpoint/scaler.pt
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last-checkpoint/scheduler.pt
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last-checkpoint/trainer_state.json
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