Instructions to use bill/bert_finetuning_test1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bill/bert_finetuning_test1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="bill/bert_finetuning_test1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("bill/bert_finetuning_test1") model = AutoModelForMaskedLM.from_pretrained("bill/bert_finetuning_test1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download MRPC/tokenizer_config.json from bill/bert_finetuning_test1: direct link, hf CLI and curl.
- Browser
- Download file 59 Bytes
-
https://huggingface.co/bill/bert_finetuning_test1/resolve/main/MRPC/tokenizer_config.json
- Command line
-
hf download hf://bill/bert_finetuning_test1/MRPC/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/bill/bert_finetuning_test1/resolve/main/MRPC/tokenizer_config.json
59 Bytes
| {"do_lower_case": false, "max_len": 512, "init_inputs": []} |