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from huggingface_hub import InferenceClient
import gradio as gr
client = InferenceClient(
"meta-llama/Meta-Llama-3-8B-Instruct"
)
punctuation_marks = [".", "!", "?"]
def generate(
prompt, history, temperature=0.2, max_new_tokens=256, top_p=0.8, 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,
)
stream = client.text_generation(prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
output = ""
for response in stream:
output += response.token.text
while output and output[-1] not in punctuation_marks:
output = output[:-1]
# yield output
return output
additional_inputs=[
gr.Slider(
label="Temperature",
value=0.2,
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=0.80,
minimum=0.0,
maximum=1,
step=0.05,
interactive=True,
info="Higher values sample more low-probability tokens",
),
gr.Slider(
label="Repetition penalty",
value=1.0,
minimum=1.0,
maximum=2.0,
step=0.05,
interactive=True,
info="Penalize repeated tokens",
)
]
gr.ChatInterface(
fn=generate,
chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
title= "Have a chat with llama 3 8B 🦙",
additional_inputs=additional_inputs,
examples=[
["Can you explain briefly to me what is the Python programming language?"],
["Write a 100-word article on 'Benefits of Open-Source in AI research'."],
],
cache_examples=True
).launch(show_api=False) |