Instructions to use WindyTranslate/translate-wal-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-wal-en with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="WindyTranslate/translate-wal-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-wal-en") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-wal-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-wal-en, with attribution and change statement
c7811ba verified - Xet hash:
- eca754b81b39926ae7f07793e8ea086782bace543c1e583b5795fa7c5872ef55
- Size of remote file:
- 862 kB
- SHA256:
- 80a58342cc89518031a26e22cec1b193fad19f0d39d7d45834500b2201429391
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