Instructions to use wallacenpj/bert_aig_flvs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wallacenpj/bert_aig_flvs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wallacenpj/bert_aig_flvs")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wallacenpj/bert_aig_flvs") model = AutoModelForSequenceClassification.from_pretrained("wallacenpj/bert_aig_flvs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from wallacenpj/bert_aig_flvs: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/wallacenpj/bert_aig_flvs/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://wallacenpj/bert_aig_flvs/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/wallacenpj/bert_aig_flvs/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- 6b6190a85f03705a0f77c66711ef902179d3429839272c8a40a05a5ac3480269
- Size of remote file:
- 433 MB
- SHA256:
- 6fac87466f7cd6317ce4dd37c86eee076d5e738858c65b1ab86ef9318c75b702
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