Instructions to use SADAF-IMAMU/train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SADAF-IMAMU/train with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SADAF-IMAMU/train")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SADAF-IMAMU/train") model = AutoModelForSequenceClassification.from_pretrained("SADAF-IMAMU/train", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from SADAF-IMAMU/train: direct link, hf CLI and curl.
- Browser
- Download file 3.9 kB
-
https://huggingface.co/SADAF-IMAMU/train/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://SADAF-IMAMU/train@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/SADAF-IMAMU/train/resolve/refs%2Fpr%2F1/training_args.bin
3.9 kB
- Xet hash:
- 002dc1694f1aa300f7505d461359e9c477ab2cb19238040b1bf5e88cc87fa3ad
- Size of remote file:
- 3.9 kB
- SHA256:
- 0a03e4b392fe4534f4ff8c5dc5501c73c0ab9cd022fc162bb3284942f6b858b3
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