Instructions to use milosdevic/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use milosdevic/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="milosdevic/results")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("milosdevic/results") model = AutoModelForSequenceClassification.from_pretrained("milosdevic/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from milosdevic/results: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/milosdevic/results/resolve/main/training_args.bin
- Command line
-
hf download hf://milosdevic/results/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/milosdevic/results/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- f0f92a97000c956c8d4dabd28dcdf064cb87902bfe4466bae23a5d7115323f53
- Size of remote file:
- 4.54 kB
- SHA256:
- 90f19cdc4bf65ae54ba131eb095db2698511c035fc242cc90b161499629bd20b
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