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 pytorch_model.bin from SADAF-IMAMU/train: direct link, hf CLI and curl.
- Browser
- Download file 541 MB
-
https://huggingface.co/SADAF-IMAMU/train/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://SADAF-IMAMU/train@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SADAF-IMAMU/train/resolve/refs%2Fpr%2F1/pytorch_model.bin
541 MB
- Xet hash:
- 71739ebdcf19aa19205ed992ae89a90e208f285a85d5793971561d7af5796484
- Size of remote file:
- 541 MB
- SHA256:
- ee4da122ef491f065be22fa00798b992e0a3af41462bc6f7206f852317946e27
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