Instructions to use dolgae03/bert_lens_1024_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dolgae03/bert_lens_1024_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dolgae03/bert_lens_1024_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dolgae03/bert_lens_1024_2") model = AutoModelForSequenceClassification.from_pretrained("dolgae03/bert_lens_1024_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee7f5592c5f706f6fa9903c61d00aab0da2828bb72eaa426a2b38f5d030da923
- Size of remote file:
- 435 MB
- SHA256:
- a60add5d477932d3a921127c0fad7f71281fac771213156d150c48276cebef91
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.