Instructions to use Alireza1044/MobileBERT_Theseus-rte with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Alireza1044/MobileBERT_Theseus-rte with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Alireza1044/MobileBERT_Theseus-rte")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Alireza1044/MobileBERT_Theseus-rte") model = AutoModelForSequenceClassification.from_pretrained("Alireza1044/MobileBERT_Theseus-rte", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Alireza1044/MobileBERT_Theseus-rte: direct link, hf CLI and curl.
- Browser
- Download file 119 MB
-
https://huggingface.co/Alireza1044/MobileBERT_Theseus-rte/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Alireza1044/MobileBERT_Theseus-rte/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Alireza1044/MobileBERT_Theseus-rte/resolve/main/pytorch_model.bin
119 MB
- Xet hash:
- b0d026a67c9a4b905c743f770612df51bbb7255c94382f9f1cd754023fe8d4cb
- Size of remote file:
- 119 MB
- SHA256:
- 84537b0dbe88dd0364efdd21a0ff4e52f0236680465b8a5db402a39a9ecf0838
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