Instructions to use ItcastAI/bert_cn_finetunning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ItcastAI/bert_cn_finetunning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ItcastAI/bert_cn_finetunning")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ItcastAI/bert_cn_finetunning") model = AutoModelForSequenceClassification.from_pretrained("ItcastAI/bert_cn_finetunning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from ItcastAI/bert_cn_finetunning: direct link, hf CLI and curl.
- Browser
- Download file 409 MB
-
https://huggingface.co/ItcastAI/bert_cn_finetunning/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://ItcastAI/bert_cn_finetunning/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/ItcastAI/bert_cn_finetunning/resolve/main/flax_model.msgpack
409 MB
- Xet hash:
- 10f48701ca73fd780e07d6a0fbce5c7ad4a82d5dcb92e957da6c5299b845da80
- Size of remote file:
- 409 MB
- SHA256:
- 2fec32b23191bddb969a9b04946e4798199ba8018709c655bf996db1fe4a1853
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