Instructions to use dlwnsdnjs/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dlwnsdnjs/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dlwnsdnjs/my_awesome_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dlwnsdnjs/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("dlwnsdnjs/my_awesome_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dlwnsdnjs/my_awesome_model: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/dlwnsdnjs/my_awesome_model/resolve/main/training_args.bin
- Command line
-
hf download hf://dlwnsdnjs/my_awesome_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dlwnsdnjs/my_awesome_model/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- cb5512dc55c078faf555ad0dec84be44800232eb167b1669f6b0ba19d949974c
- Size of remote file:
- 4.98 kB
- SHA256:
- d0a7f94aa73901447d7023b4cf7ea6c3b338f86c288953d92b51894d99f8a51f
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