Update app.py
Browse files
app.py
CHANGED
@@ -1,8 +1,8 @@
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from transformers import
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MODEL_NAME_OR_PATH = "
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tokenizer =
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model =
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prefix = "items: "
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generation_kwargs = {
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@@ -15,12 +15,6 @@ generation_kwargs = {
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"num_return_sequences": 1
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}
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special_tokens = tokenizer.all_special_tokens
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tokens_map = {
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"<sep>": "--",
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"<section>": "\n"
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}
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def skip_special_tokens(text, special_tokens):
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for token in special_tokens:
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text = text.replace(token, "")
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@@ -32,8 +26,6 @@ def target_postprocessing(texts, special_tokens):
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new_texts = []
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for text in texts:
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text = skip_special_tokens(text, special_tokens)
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for k, v in tokens_map.items():
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text = text.replace(k, v)
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new_texts.append(text)
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return new_texts
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@@ -44,18 +36,18 @@ def generate_recipe(items):
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max_length=256,
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padding="max_length",
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truncation=True,
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return_tensors="
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)
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input_ids = inputs.input_ids
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attention_mask = inputs.attention_mask
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output_ids = model.generate(
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input_ids=input_ids,
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attention_mask=attention_mask,
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**generation_kwargs
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)
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generated_recipe =
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generated_recipe = target_postprocessing(generated_recipe, special_tokens)
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return generated_recipe[0]
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# Example usage
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from transformers import T5Tokenizer, FlaxT5ForConditionalGeneration
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MODEL_NAME_OR_PATH = "t5-base"
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tokenizer = T5Tokenizer.from_pretrained(MODEL_NAME_OR_PATH)
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model = FlaxT5ForConditionalGeneration.from_pretrained(MODEL_NAME_OR_PATH)
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prefix = "items: "
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generation_kwargs = {
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"num_return_sequences": 1
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}
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def skip_special_tokens(text, special_tokens):
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for token in special_tokens:
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text = text.replace(token, "")
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new_texts = []
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for text in texts:
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text = skip_special_tokens(text, special_tokens)
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new_texts.append(text)
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return new_texts
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max_length=256,
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padding="max_length",
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truncation=True,
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return_tensors="jax"
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)
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input_ids = inputs.input_ids
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attention_mask = inputs.attention_mask
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output_ids = model.generate(
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input_ids=input_ids,
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attention_mask=attention_mask,
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**generation_kwargs
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)
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generated_recipe = tokenizer.batch_decode(output_ids, skip_special_tokens=False)
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generated_recipe = target_postprocessing(generated_recipe, tokenizer.all_special_tokens)
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return generated_recipe[0]
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# Example usage
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