Instructions to use Gnider/rubert_tiny_5ep_weights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gnider/rubert_tiny_5ep_weights with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Gnider/rubert_tiny_5ep_weights")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Gnider/rubert_tiny_5ep_weights") model = AutoModelForSequenceClassification.from_pretrained("Gnider/rubert_tiny_5ep_weights", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download wandb/debug-internal.log from Gnider/rubert_tiny_5ep_weights: direct link, hf CLI and curl.
- Browser
- Download file 609 kB
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https://huggingface.co/Gnider/rubert_tiny_5ep_weights/resolve/main/wandb/debug-internal.log
- Command line
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hf download hf://Gnider/rubert_tiny_5ep_weights/wandb/debug-internal.log
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curl -L -o debug-internal.log https://huggingface.co/Gnider/rubert_tiny_5ep_weights/resolve/main/wandb/debug-internal.log
609 kB
File too large to display, you can check the raw version instead.