Instructions to use jmmr-8282/email with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jmmr-8282/email with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jmmr-8282/email")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jmmr-8282/email") model = AutoModelForSequenceClassification.from_pretrained("jmmr-8282/email") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 3, 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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"best_model_checkpoint": "./bert-email/checkpoint-
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"is_world_process_zero": true,
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"eval_samples_per_second": 55.783,
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"eval_samples_per_second": 55.783,
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