Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use ben-yu/roberta-base-finetuned-nlp-letters-s1_s2-all-class-weighted with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ben-yu/roberta-base-finetuned-nlp-letters-s1_s2-all-class-weighted with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ben-yu/roberta-base-finetuned-nlp-letters-s1_s2-all-class-weighted")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ben-yu/roberta-base-finetuned-nlp-letters-s1_s2-all-class-weighted") model = AutoModelForSequenceClassification.from_pretrained("ben-yu/roberta-base-finetuned-nlp-letters-s1_s2-all-class-weighted", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ben-yu/roberta-base-finetuned-nlp-letters-s1_s2-all-class-weighted: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/ben-yu/roberta-base-finetuned-nlp-letters-s1_s2-all-class-weighted/resolve/main/training_args.bin
- Command line
-
hf download hf://ben-yu/roberta-base-finetuned-nlp-letters-s1_s2-all-class-weighted/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ben-yu/roberta-base-finetuned-nlp-letters-s1_s2-all-class-weighted/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- fdcad7b656c06ab15130563d7f0049874dad33226eed393d843a9e1fb03b3e8d
- Size of remote file:
- 5.24 kB
- SHA256:
- 9773f14158059d4c75a82d32b6de086b4d29a3c36aa6d6805c4db146a6f4216f
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