Instructions to use egomal/training_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use egomal/training_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="egomal/training_output")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("egomal/training_output") model = AutoModelForSequenceClassification.from_pretrained("egomal/training_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from egomal/training_output: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/egomal/training_output/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://egomal/training_output/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/egomal/training_output/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 8f7e5f8f3cad5d96034b41d20d48b7e392423d4c2ef7e5b8f790785cad639480
- Size of remote file:
- 499 MB
- SHA256:
- ef9bf9ecfc1da46e7e48ad7a760b4c9d556f73c037c99325214b03e13e459c8a
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