Instructions to use ElMad/crawling-koi-710 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ElMad/crawling-koi-710 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ElMad/crawling-koi-710")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ElMad/crawling-koi-710") model = AutoModelForSequenceClassification.from_pretrained("ElMad/crawling-koi-710", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ElMad/crawling-koi-710: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/ElMad/crawling-koi-710/resolve/main/training_args.bin
- Command line
-
hf download hf://ElMad/crawling-koi-710/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ElMad/crawling-koi-710/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- d4739f425a551d34d2b44f05a531fd0dd791209ff3c5aa9c336ee27fba65d4ed
- Size of remote file:
- 5.37 kB
- SHA256:
- 94ffc0409dfb9dcea5ede17034bede3ba9eeb0853f7a5c4d1815d85a4e555fcd
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