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Update README.md

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  <!-- Provide a longer summary of what this model is. -->
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- - **Developed by:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Model type:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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- - **License:** [More Information Needed]
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- - **Finetuned from model [optional]:** [More Information Needed]
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- ### Model Sources [optional]
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- <!-- Provide the basic links for the model. -->
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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  ## Uses
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- ```
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- gen_kwargs = {
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  "max_new_tokens": 100,
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  "top_k": 70,
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  "top_p": 0.8,
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  prepared = tokenizer.encode(inp, return_tensors='pt').to(model.device)
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  out = model.generate(input_ids=prepared, **gen_kwargs)
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  generated = tokenizer.decode(out[0])
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- ```
 
 
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  <!-- Provide a longer summary of what this model is. -->
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  ## Uses
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+ <!-- gen_kwargs = {
 
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  "max_new_tokens": 100,
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  "top_k": 70,
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  "top_p": 0.8,
 
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  prepared = tokenizer.encode(inp, return_tensors='pt').to(model.device)
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  out = model.generate(input_ids=prepared, **gen_kwargs)
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  generated = tokenizer.decode(out[0])
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+ -->
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