Instructions to use skumar1998/result with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use skumar1998/result with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("skumar1998/result", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Model save
Browse files
file.log
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@@ -41,3 +41,4 @@ Dataset Split Statistics:
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2026-07-26 19:43:06.171 | INFO | __main__:create_trainer:282 - Datasets: 4250 train, 563 eval samples
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2026-07-26 19:43:06.979 | INFO | __main__:standard_training_loop:336 - Starting training
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2026-07-26 19:43:07.183 | INFO | app.tasks.entity.vlm.model:train_model:600 - everything is set up, launching training
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2026-07-26 19:43:06.171 | INFO | __main__:create_trainer:282 - Datasets: 4250 train, 563 eval samples
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2026-07-26 19:43:06.979 | INFO | __main__:standard_training_loop:336 - Starting training
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2026-07-26 19:43:07.183 | INFO | app.tasks.entity.vlm.model:train_model:600 - everything is set up, launching training
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2026-07-27 03:10:51.427 | INFO | app.tasks.entity.vlm.model:train_model:606 - training complete: TrainOutput(global_step=530, training_loss=0.057691663363069856, metrics={'train_runtime': 26848.6091, 'train_samples_per_second': 0.316, 'train_steps_per_second': 0.02, 'total_flos': 2.7079361524323604e+18, 'train_loss': 0.057691663363069856, 'epoch': 1.9934148635936029})
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runs/Jul26_19-43-09_8b035ff02fbe/events.out.tfevents.1785094989.8b035ff02fbe.9449.0
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version https://git-lfs.github.com/spec/v1
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size 32415
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