SantiagoMoreno-Col commited on
Commit
aa79c62
Β·
1 Parent(s): fc4acd6
Files changed (2) hide show
  1. app.py +23 -19
  2. requirements.txt +2 -1
app.py CHANGED
@@ -1,11 +1,12 @@
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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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  client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
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-
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  def respond(
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  message,
@@ -15,29 +16,32 @@ def respond(
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  temperature,
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  top_p,
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  ):
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- messages = [{"role": "system", "content": system_message}]
 
 
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- for val in history:
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- if val[0]:
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- messages.append({"role": "user", "content": val[0]})
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- if val[1]:
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- messages.append({"role": "assistant", "content": val[1]})
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- messages.append({"role": "user", "content": message})
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- response = ""
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- for message in client.chat_completion(
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- messages,
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- max_tokens=max_tokens,
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- stream=True,
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- temperature=temperature,
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- top_p=top_p,
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- ):
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- token = message.choices[0].delta.content
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- response += token
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- yield response
 
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  """
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  For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
 
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  import gradio as gr
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  from huggingface_hub import InferenceClient
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+ from transformers import pipeline
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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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  client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
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+ pipe = pipeline("text-generation", model="HiTZ/latxa-7b-v1")
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  def respond(
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  message,
 
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  temperature,
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  top_p,
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  ):
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+
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+ message = pipe(system_message, max_new_tokens=50, num_beams=5)
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+ # messages = [{"role": "system", "content": system_message}]
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+ # for val in history:
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+ # if val[0]:
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+ # messages.append({"role": "user", "content": val[0]})
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+ # if val[1]:
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+ # messages.append({"role": "assistant", "content": val[1]})
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+ # messages.append({"role": "user", "content": message})
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+ # response = ""
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+ # for message in client.chat_completion(
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+ # messages,
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+ # max_tokens=max_tokens,
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+ # stream=True,
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+ # temperature=temperature,
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+ # top_p=top_p,
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+ # ):
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+ # token = message.choices[0].delta.content
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+ # response += token
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+ # yield response
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+ return message
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  """
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  For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
requirements.txt CHANGED
@@ -1 +1,2 @@
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- huggingface_hub==0.22.2
 
 
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+ huggingface_hub==0.22.2
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+ transformers