Instructions to use Wzf/bert_fintuuing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wzf/bert_fintuuing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Wzf/bert_fintuuing")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Wzf/bert_fintuuing") model = AutoModelForMaskedLM.from_pretrained("Wzf/bert_fintuuing", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Wzf/bert_fintuuing: direct link, hf CLI and curl.
- Browser
- Download file 409 MB
-
https://huggingface.co/Wzf/bert_fintuuing/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Wzf/bert_fintuuing/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Wzf/bert_fintuuing/resolve/main/pytorch_model.bin
409 MB
- Xet hash:
- ba04681e36aecc24a4616f2e99779273c878b58dc717d59f13d475ca2f50582a
- Size of remote file:
- 409 MB
- SHA256:
- ce78e58fb25fc6b0cb03a3b26f34d5efb59df09706d5386f1283a9ede5fd46e3
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