Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use namesarnav/causalbench_math-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use namesarnav/causalbench_math-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="namesarnav/causalbench_math-roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("namesarnav/causalbench_math-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("namesarnav/causalbench_math-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from namesarnav/causalbench_math-roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 5.91 kB
-
https://huggingface.co/namesarnav/causalbench_math-roberta-base/resolve/main/training_args.bin
- Command line
-
hf download hf://namesarnav/causalbench_math-roberta-base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/namesarnav/causalbench_math-roberta-base/resolve/main/training_args.bin
5.91 kB
- Xet hash:
- 77bbc65923fd52355e0214b21fa7f63e95b85454a69c572b2a5022f09322c764
- Size of remote file:
- 5.91 kB
- SHA256:
- fa5d4f5bf8f0bdec1959fed9440baa0ce905693831c4fe3cf6b5484c0ca90f26
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