Update README.md
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Blunt2531
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README.md
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---
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license:
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language:
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- en
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library_name:
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pipeline_tag:
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tags:
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- multimodal
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- aria
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---
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<!-- <p align="center">
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<br>Aria</br>
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@@ -103,11 +113,11 @@ inputs = {k: v.to(model.device) for k, v in inputs.items()}
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with torch.inference_mode(), torch.cuda.amp.autocast(dtype=torch.bfloat16):
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output = model.generate(
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**inputs,
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max_new_tokens=
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stop_strings=["<|im_end|>"],
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tokenizer=processor.tokenizer,
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do_sample=True,
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temperature=
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)
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output_ids = output[0][inputs["input_ids"].shape[1]:]
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result = processor.decode(output_ids, skip_special_tokens=True)
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---
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license: creativeml-openrail-m
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language:
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- en
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library_name: fasttext
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pipeline_tag: any-to-any
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tags:
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- multimodal
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- aria
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datasets:
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- fka/awesome-chatgpt-prompts
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- nvidia/OpenMathInstruct-2
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- neuralwork/arxiver
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metrics:
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- accuracy
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- bertscore
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base_model:
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- black-forest-labs/FLUX.1-dev
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new_version: openai/whisper-large-v3-turbo
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---
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<!-- <p align="center">
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<br>Aria</br>
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with torch.inference_mode(), torch.cuda.amp.autocast(dtype=torch.bfloat16):
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output = model.generate(
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**inputs,
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max_new_tokens=99999,
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stop_strings=["<|im_end|>"],
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tokenizer=processor.tokenizer,
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do_sample=True,
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temperature=1.9,
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)
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output_ids = output[0][inputs["input_ids"].shape[1]:]
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result = processor.decode(output_ids, skip_special_tokens=True)
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