Translation
Transformers
PyTorch
JAX
Russian
Kabardian
t5
text2text-generation
text-generation-inference
Instructions to use anzorq/kbd_lat-ru_char_tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anzorq/kbd_lat-ru_char_tokenizer 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="anzorq/kbd_lat-ru_char_tokenizer")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("anzorq/kbd_lat-ru_char_tokenizer") model = AutoModelForSeq2SeqLM.from_pretrained("anzorq/kbd_lat-ru_char_tokenizer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 314d6f2c05b4dcfc59618662535d006b22c102f83baa374d538011c2a5549bbf
- Size of remote file:
- 818 MB
- SHA256:
- afaed42da6a57b05579a78a93c78df7d1cbde25606de6bd4ff7a3795d539fe41
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