Translation
Transformers
PyTorch
ONNX
Safetensors
m2m_100
text2text-generation
small100
flores101
gsarti/flores_101
tico19
gmnlp/tico19
tatoeba
Instructions to use alirezamsh/small100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alirezamsh/small100 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="alirezamsh/small100")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("alirezamsh/small100") model = AutoModelForSeq2SeqLM.from_pretrained("alirezamsh/small100") - Inference
- Notebooks
- Google Colab
- Kaggle
Attribute name incorrect
#16
by LiPengtao12138 - opened
Only src_lang can be used to refer to the target language, using tgt_lang is invalid.
def t2t_small100(text, source_language = None, target_language = None):
model_small100_tokenizer.src_lang = target_language
# model_small100_tokenizer.tgt_lang = target_language # invalid
encoded_text = model_small100_tokenizer(text, return_tensors="pt")
generated_tokens = model_small100.generate(**encoded_text)
predict_text = model_small100_tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0]