Instructions to use Frorozcol/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Frorozcol/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Frorozcol/results")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Frorozcol/results") model = AutoModelForSequenceClassification.from_pretrained("Frorozcol/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-3000/optimizer.pt from Frorozcol/results: direct link, hf CLI and curl.
- Browser
- Download file 93.5 MB
-
https://huggingface.co/Frorozcol/results/resolve/main/checkpoint-3000/optimizer.pt
- Command line
-
hf download hf://Frorozcol/results/checkpoint-3000/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Frorozcol/results/resolve/main/checkpoint-3000/optimizer.pt
93.5 MB
- Xet hash:
- e2820478c80901d47c51794afc7d8187bb1db088f546e7ddf05313e59458cdd2
- Size of remote file:
- 93.5 MB
- SHA256:
- 420dd64f23e2b68d1b1b96356faa6548bd8615714a986e6ee6234b2a4491c8d8
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