Instructions to use gurkan08/bert-turkish-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gurkan08/bert-turkish-text-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gurkan08/bert-turkish-text-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gurkan08/bert-turkish-text-classification") model = AutoModelForSequenceClassification.from_pretrained("gurkan08/bert-turkish-text-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from gurkan08/bert-turkish-text-classification: direct link, hf CLI and curl.
- Browser
- Download file 442 MB
-
https://huggingface.co/gurkan08/bert-turkish-text-classification/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://gurkan08/bert-turkish-text-classification/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/gurkan08/bert-turkish-text-classification/resolve/main/flax_model.msgpack
442 MB
- Xet hash:
- 44feec580eb0eaabda89f60427fa9a5085d1edd12014a312d3bb75a84933309d
- Size of remote file:
- 442 MB
- SHA256:
- 926d00f09445f904c5c4e61dd21ec14be8e373e6573a5ebd3458addd3e5af331
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.