Instructions to use k4black/Salesforce-codet5-small-CodeXGLUE-CONCODE-adamw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use k4black/Salesforce-codet5-small-CodeXGLUE-CONCODE-adamw with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("k4black/Salesforce-codet5-small-CodeXGLUE-CONCODE-adamw") model = AutoModelForSeq2SeqLM.from_pretrained("k4black/Salesforce-codet5-small-CodeXGLUE-CONCODE-adamw", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 11000
Browse files- last-checkpoint/optimizer.pt +1 -1
- last-checkpoint/pytorch_model.bin +1 -1
- last-checkpoint/rng_state.pth +1 -1
- last-checkpoint/scaler.pt +1 -1
- last-checkpoint/scheduler.pt +1 -1
- last-checkpoint/trainer_state.json +23 -3
- pytorch_model.bin +1 -1
last-checkpoint/optimizer.pt
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last-checkpoint/pytorch_model.bin
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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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"eval_samples_per_second": 70.971,
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pytorch_model.bin
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