Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Yuvrajg2107/roberta-base-cpp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yuvrajg2107/roberta-base-cpp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Yuvrajg2107/roberta-base-cpp")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Yuvrajg2107/roberta-base-cpp") model = AutoModelForSequenceClassification.from_pretrained("Yuvrajg2107/roberta-base-cpp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from Yuvrajg2107/roberta-base-cpp: direct link, hf CLI and curl.
- Browser
- Download file 997 MB
-
https://huggingface.co/Yuvrajg2107/roberta-base-cpp/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://Yuvrajg2107/roberta-base-cpp/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Yuvrajg2107/roberta-base-cpp/resolve/main/last-checkpoint/optimizer.pt
997 MB
- Xet hash:
- 4e47b8dc567380ce44b5a789189f71d94acd7f9ba045b219fa0d13d8d7fe58bf
- Size of remote file:
- 997 MB
- SHA256:
- 500ffd76170b7fb618ea379239932a47631205a4d9705066b56afb09614f681d
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