Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
zero-shot_classification
text-embeddings-inference
Instructions to use adriansanz/test6_balanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adriansanz/test6_balanced with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="adriansanz/test6_balanced")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("adriansanz/test6_balanced") model = AutoModelForSequenceClassification.from_pretrained("adriansanz/test6_balanced", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from adriansanz/test6_balanced: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/adriansanz/test6_balanced/resolve/main/training_args.bin
- Command line
-
hf download hf://adriansanz/test6_balanced/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/adriansanz/test6_balanced/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 270dc2b320d3d13c671932bdbf7e71f6b224241a86967753ad2ccf0af0584ea7
- Size of remote file:
- 4.92 kB
- SHA256:
- 212893120ff547f79a17dbdec269e1f33b50320ef3315be8538a513d73c3b810
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