Instructions to use MaagDeveloper/rust_python_roberta_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MaagDeveloper/rust_python_roberta_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MaagDeveloper/rust_python_roberta_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MaagDeveloper/rust_python_roberta_classifier") model = AutoModelForSequenceClassification.from_pretrained("MaagDeveloper/rust_python_roberta_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from MaagDeveloper/rust_python_roberta_classifier: direct link, hf CLI and curl.
- Browser
- Download file 32.3 MB
-
https://huggingface.co/MaagDeveloper/rust_python_roberta_classifier/resolve/main/model.safetensors
- Command line
-
hf download hf://MaagDeveloper/rust_python_roberta_classifier/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/MaagDeveloper/rust_python_roberta_classifier/resolve/main/model.safetensors
32.3 MB
- Xet hash:
- 1259e856c9282c37dee3b0b688f84080490f7c3209a572b500079156e4972e39
- Size of remote file:
- 32.3 MB
- SHA256:
- 3f7ffd8792fe742ad1d838e70bd13317c15d63ac22f99ea146fad95cf7201f1b
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