Translation
Transformers
PyTorch
Enawené-Nawé
Enawené-Nawé
mt5
text2text-generation
Trained with AutoTrain
Instructions to use Tritkoman/EnglishtoRusynV2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tritkoman/EnglishtoRusynV2 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="Tritkoman/EnglishtoRusynV2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Tritkoman/EnglishtoRusynV2") model = AutoModelForSeq2SeqLM.from_pretrained("Tritkoman/EnglishtoRusynV2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Tritkoman/EnglishtoRusynV2: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/Tritkoman/EnglishtoRusynV2/resolve/main/tokenizer.json
- Command line
-
hf download hf://Tritkoman/EnglishtoRusynV2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Tritkoman/EnglishtoRusynV2/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- 3f262bbb8e6a9fbde446ce52672b8ddb365af08db1349638ab01d51fbe5cb856
- Size of remote file:
- 16.3 MB
- SHA256:
- 5cae99066d4f7bc0a506a3cfb9be43a7caaf2a3a19dc38b2f00fadff37981b52
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