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README.md
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- **Developed by:** Dongjun Kim
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- **Model type:** Text2Text Generation
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- **Language(s) (NLP):** English
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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## Intended Uses
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```python
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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tokenizer = AutoTokenizer.from_pretrained("
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model = AutoModelForSeq2SeqLM.from_pretrained("
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gloss_input = "YOU GO STORE TOMORROW?"
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inputs = tokenizer(gloss_input, return_tensors="pt")
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output = model.generate(**inputs)
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print(tokenizer.decode(output[0], skip_special_tokens=True))
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```
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## Bias, Risks, and Limitations
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- **Developed by:** Dongjun Kim
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- **Model type:** Text2Text Generation
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- **Language(s) (NLP):** English
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## Intended Uses
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```python
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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tokenizer = AutoTokenizer.from_pretrained("rrrr66254/bart-gloss-finetuned")
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model = AutoModelForSeq2SeqLM.from_pretrained("rrrr66254/bart-gloss-finetuned")
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gloss_input = "YOU GO STORE TOMORROW?"
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inputs = tokenizer(gloss_input, return_tensors="pt")
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output = model.generate(**inputs)
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print(tokenizer.decode(output[0], skip_special_tokens=True))
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# Expected output is "Are you going to the store tomorrow?"
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```
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## Bias, Risks, and Limitations
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