Instructions to use lvwerra/bert-imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lvwerra/bert-imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lvwerra/bert-imdb")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lvwerra/bert-imdb") model = AutoModelForSequenceClassification.from_pretrained("lvwerra/bert-imdb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from lvwerra/bert-imdb: direct link, hf CLI and curl.
- Browser
- Download file 1.33 GB
-
https://huggingface.co/lvwerra/bert-imdb/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://lvwerra/bert-imdb/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/lvwerra/bert-imdb/resolve/main/flax_model.msgpack
1.33 GB
- Xet hash:
- 127414b3cc615744261ff5c795821d9898e3979179053b0fee427ad3d93c2f2e
- Size of remote file:
- 1.33 GB
- SHA256:
- c18412fc41f204851b2654075cc3f060a010e83c36aa3bc7d21a7d53568d8c3a
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