Files changed (1) hide show
  1. app.py +36 -0
app.py CHANGED
@@ -1,6 +1,42 @@
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  import gradio as gr
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  from huggingface_hub import InferenceClient
 
 
 
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  """
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  For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
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  """
 
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  import gradio as gr
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  from huggingface_hub import InferenceClient
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+ ##############################################################
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+ import torch
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+ from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
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+ torch.random.manual_seed(0)
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+ model = AutoModelForCausalLM.from_pretrained(
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+ "microsoft/Phi-3-mini-128k-instruct",
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+ device_map="cuda",
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+ torch_dtype="auto",
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+ trust_remote_code=True,
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+ )
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+
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+ tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-128k-instruct")
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+
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+ messages = [
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+ {"role": "system", "content": "You are a helpful AI assistant."},
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+ {"role": "user", "content": "Can you provide ways to eat combinations of bananas and dragonfruits?"},
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+ {"role": "assistant", "content": "Sure! Here are some ways to eat bananas and dragonfruits together: 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey. 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey."},
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+ {"role": "user", "content": "What about solving an 2x + 3 = 7 equation?"},
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+ ]
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+
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+ pipe = pipeline(
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+ "text-generation",
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+ model=model,
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+ tokenizer=tokenizer,
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+ )
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+
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+ generation_args = {
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+ "max_new_tokens": 500,
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+ "return_full_text": False,
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+ "temperature": 0.0,
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+ "do_sample": False,
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+ }
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+
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+ output = pipe(messages, **generation_args)
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+ print(output[0]['generated_text'])
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+ ##############################################################
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  """
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  For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
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  """