Instructions to use tals/roberta_python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tals/roberta_python with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tals/roberta_python")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tals/roberta_python") model = AutoModelForMaskedLM.from_pretrained("tals/roberta_python", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from tals/roberta_python: direct link, hf CLI and curl.
- Browser
- Download file 501 MB
-
https://huggingface.co/tals/roberta_python/resolve/refs%2Fpr%2F2/model.safetensors
- Command line
-
hf download hf://tals/roberta_python@refs/pr/2/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/tals/roberta_python/resolve/refs%2Fpr%2F2/model.safetensors
501 MB
- Xet hash:
- 8736a51e13092548ef053f5266e41c658a7a58607e9e112e944a44d5cc72d637
- Size of remote file:
- 501 MB
- SHA256:
- 4d26c745ac740491f709243e33bf096a9e5f0baba02a40d215d027f666faac60
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