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Update app.py
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app.py
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@@ -2,13 +2,14 @@
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#!pip install transformers gradio accelerate bitsandbytes sentencepiece
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import multiprocessing
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import torch
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from transformers import T5Tokenizer, T5ForConditionalGeneration
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import gradio as gr
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"""#Code"""
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device = "cuda:0" if torch.cuda.is_available() else "cpu"
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"""##FP 16"""
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@@ -19,7 +20,7 @@ model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-xl", device_m
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"""###Interface"""
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def generate(input_text, minimum_length, maximum_length, temperature, repetition_penalty):
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input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(dtype=torch.
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outputs = model.generate(input_ids,
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min_length=minimum_length,
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max_new_tokens=maximum_length,
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#!pip install transformers gradio accelerate bitsandbytes sentencepiece
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#import multiprocessing
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import torch
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from transformers import T5Tokenizer, T5ForConditionalGeneration
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import gradio as gr
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"""#Code"""
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torch.set_default_dtype(torch.float16)
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device = "cuda:0" if torch.cuda.is_available() else "cpu"
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"""##FP 16"""
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"""###Interface"""
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def generate(input_text, minimum_length, maximum_length, temperature, repetition_penalty):
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input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(dtype=torch.long).to(device)
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outputs = model.generate(input_ids,
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min_length=minimum_length,
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max_new_tokens=maximum_length,
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