Instructions to use ItcastAI/bert_finetunning_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ItcastAI/bert_finetunning_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ItcastAI/bert_finetunning_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ItcastAI/bert_finetunning_test") model = AutoModelForSequenceClassification.from_pretrained("ItcastAI/bert_finetunning_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from ItcastAI/bert_finetunning_test: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/ItcastAI/bert_finetunning_test/resolve/refs%2Fpr%2F1/flax_model.msgpack
- Command line
-
hf download hf://ItcastAI/bert_finetunning_test@refs/pr/1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/ItcastAI/bert_finetunning_test/resolve/refs%2Fpr%2F1/flax_model.msgpack
438 MB
- Xet hash:
- 9edf3735d0f3edf1fe46c7ff79c565e756dada5ad73b31609d88e7b9ebaccdd6
- Size of remote file:
- 438 MB
- SHA256:
- 264f9d724bf5bc6b730b023b19ac507e861f8ff76e0c16c18d884d9659a2e5c8
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