Translation
Transformers
Safetensors
English
Krio
mbart
text2text-generation
machine-translation
mbart-50
krio
sierra-leone
low-resource
Instructions to use MosesJoshuaCoker/text-to-text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MosesJoshuaCoker/text-to-text 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="MosesJoshuaCoker/text-to-text")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("MosesJoshuaCoker/text-to-text") model = AutoModelForSeq2SeqLM.from_pretrained("MosesJoshuaCoker/text-to-text") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a8251f7fb37e3b2236e69277f3e6d4190e9376912a1dc6baf18e8680174c2b4
- Size of remote file:
- 17.1 MB
- SHA256:
- 0e301b8f685ce732c83295af6db0921e39453113fdc839f3d605646b84c2cc16
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