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from huggingface_hub import InferenceClient
import gradio as gr
client = InferenceClient(
"mistralai/Mistral-7B-Instruct-v0.1"
)
def format_prompt(message, history):
prompt = "<s>"
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
additional_inputs=[
gr.Slider(
label="Temperature",
value=0.9,
minimum=0.0,
maximum=1.0,
step=0.05,
interactive=True,
info="Higher values produce more diverse outputs",
),
gr.Slider(
label="Max new tokens",
value=256,
minimum=0,
maximum=1048,
step=64,
interactive=True,
info="The maximum numbers of new tokens",
),
gr.Slider(
label="Top-p (nucleus sampling)",
value=0.90,
minimum=0.0,
maximum=1,
step=0.05,
interactive=True,
info="Higher values sample more low-probability tokens",
),
gr.Slider(
label="Repetition penalty",
value=1.2,
minimum=1.0,
maximum=2.0,
step=0.05,
interactive=True,
info="Penalize repeated tokens",
)
]
css = """
#mkd {
height: 500px;
overflow: auto;
border: 1px solid #ccc;
}
"""
with gr.Blocks(css=css) as demo:
gr.HTML("""π€ Mistral 7B Instruct π€
In this demo, you can chat with <a href='https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1'>Mistral-7B-Instruct</a> model. π¬
π Model Features π
<ul>
<li>πͺ Sliding Window Attention with 128K tokens span</li>
<li>π GQA for faster inference</li>
<li>π Byte-fallback BPE tokenizer</li>
</ul>
π License π Released under Apache 2.0 License
π¦ Usage π¦
<ul>
<li>π Available on Huggingface Hub</li>
<li>π Python code snippets for easy setup</li>
<li>π Expected speedups with Flash Attention 2</li>
</ul>
Learn more about the model <a href='https://huggingface.co/docs/transformers/main/model_doc/mistral'>here</a>. π
""")
gr.ChatInterface(
generate,
additional_inputs=additional_inputs,
examples=[
["Create a ten-point markdown outline with emojis about: Decreased Ξ±-ketoglutarate dehydrogenase activity in astrocytes"],
["Create a ten-point markdown outline with emojis about: Lewy body dementia"],
["Create a ten-point markdown outline with emojis about: Delusional disorder"],
["Create a ten-point markdown outline with emojis about: Galantamine"],
["Create a ten-point markdown outline with emojis about: Neural crest"],
["Create a ten-point markdown outline with emojis about: Progressive multifocal encephalopathy (PML)"],
["Create a ten-point markdown outline with emojis about: CT head"],
["Create a ten-point markdown outline with emojis about: Ξ²-Galactocerebrosidase"],
["Create a ten-point markdown outline with emojis about: Dopamine"],
["Create a ten-point markdown outline with emojis about: G protein-coupled receptors"],
["Create a ten-point markdown outline with emojis about: CT scan of the head without contrast"],
["Create a ten-point markdown outline with emojis about: Pyogenic brain abscess"],
["Create a ten-point markdown outline with emojis about: Pneumocystitis jiroveci"]
]
)
demo.queue().launch(debug=True) |