Instructions to use eduagarcia-temp/brwac_v1_5__checkpoint_22_80000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eduagarcia-temp/brwac_v1_5__checkpoint_22_80000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="eduagarcia-temp/brwac_v1_5__checkpoint_22_80000")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("eduagarcia-temp/brwac_v1_5__checkpoint_22_80000") model = AutoModelForMaskedLM.from_pretrained("eduagarcia-temp/brwac_v1_5__checkpoint_22_80000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
ec33232 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:c542bce05aa8e0caf0bb5e183573e913ed99389e736787fc754685a65dcb4658
size 498829122
|