Instructions to use burmaxwell/Bert_temp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use burmaxwell/Bert_temp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="burmaxwell/Bert_temp")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("burmaxwell/Bert_temp") model = AutoModelForSequenceClassification.from_pretrained("burmaxwell/Bert_temp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from burmaxwell/Bert_temp: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/burmaxwell/Bert_temp/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://burmaxwell/Bert_temp/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/burmaxwell/Bert_temp/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- d2a832b08165ff77919feca65ca0aa86cfec73b065b192ac190e63e55df2ff58
- Size of remote file:
- 438 MB
- SHA256:
- 98f431c0f5e6b6051412d7a8a2f07c29c95873d33ca47e6ed2592838e5cd1acd
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