Instructions to use PubChimps/dlfBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PubChimps/dlfBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PubChimps/dlfBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PubChimps/dlfBERT") model = AutoModelForSequenceClassification.from_pretrained("PubChimps/dlfBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from PubChimps/dlfBERT: direct link, hf CLI and curl.
- Browser
- Download file 334 MB
-
https://huggingface.co/PubChimps/dlfBERT/resolve/refs%2Fpr%2F1/flax_model.msgpack
- Command line
-
hf download hf://PubChimps/dlfBERT@refs/pr/1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/PubChimps/dlfBERT/resolve/refs%2Fpr%2F1/flax_model.msgpack
334 MB
- Xet hash:
- 3a8cecd849cee133c77c21ac9d79f5582997bdbfd19143593f7a47555ddf38fb
- Size of remote file:
- 334 MB
- SHA256:
- 15c2140a855c0b28663137344ecd87cdb9a85509c00adb5546c04b2176cdc34c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.