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from huggingface_hub import InferenceClient
import gradio as gr
client = InferenceClient(
"mistralai/Mistral-7B-Instruct-v0.3"
)
# Your system prompt
SYSTEM_PROMPT = "Your goal is to create engaging, authentic, and contextually appropriate captions for social media platforms. The captions should captivate the audience without being cringe-worthy, ensuring they resonate well with diverse demographics."
def format_prompt(message, history):
prompt = "<s>"
prompt += f"[INST] SYSTEM: {SYSTEM_PROMPT} [/INST]" # Add the system prompt here
for user_prompt, bot_response in history:
prompt += f"[INST] {user_prompt} [/INST]"
prompt += f" {bot_response}</s> "
prompt += f"[INST] {message} [/INST]"
return prompt
def generate(
prompt, history=[], temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0,
):
temperature = float(temperature)
if temperature < 1e-2:
temperature = 1e-2
top_p = float(top_p)
generate_kwargs = dict(
temperature=temperature,
max_new_tokens=max_new_tokens,
top_p=top_p,
repetition_penalty=repetition_penalty,
do_sample=True,
seed=42,
)
formatted_prompt = format_prompt(prompt, history)
stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
output = ""
for response in stream:
output += response.token.text
yield output
return output
iface = gr.Interface(
fn=generate,
inputs=[
gr.Textbox(placeholder="Enter your prompt here...", lines=2, max_lines=2, label=""),
gr.Button("Generate")
],
outputs=gr.Textbox(label="Output", interactive=True, lines=10),
layout="vertical"
)
iface.launch()
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