Spaces:
Running
on
Zero
Running
on
Zero
File size: 3,784 Bytes
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import spaces
from transformers import AutoTokenizer, AutoModelForCausalLM, TextIteratorStreamer
from threading import Thread
import gradio as gr
import torch
import os
device = "cuda"
model_name = "mistralai/mathstral-7B-v0.1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name,
torch_dtype=torch.float16).to(device)
HF_TOKEN = os.environ['HF_TOKEN']
def format_prompt(message, history):
prompt = ""
for user_prompt, bot_response in history:
prompt += f"[INST] {user_prompt} [/INST]"
prompt += f" {bot_response} "
prompt += f"[INST] {message} [/INST]"
return prompt
@spaces.GPU
def generate(prompt, history,
max_new_tokens=1024,
repetition_penalty=1.2):
formatted_prompt = format_prompt(prompt, history)
inputs = tokenizer(formatted_prompt, return_tensors="pt").to(device)
streamer = TextIteratorStreamer(tokenizer)
generate_kwargs = dict(
inputs,
streamer=streamer,
max_new_tokens=max_new_tokens,
repetition_penalty=repetition_penalty,
)
thread = Thread(target=model.generate, kwargs=generate_kwargs)
thread.start()
text = ''
n = len('<s>') + len(formatted_prompt)
for word in streamer:
text += word
yield text[n:]
return text[n:]
additional_inputs=[
gr.Slider(
label="Max new tokens",
value=1024,
minimum=0,
maximum=4096,
step=256,
interactive=True,
info="The maximum numbers of new 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("<h1><center>Mathstral Test</center><h1>")
gr.HTML("<h3><center>Dans cette démo, vous pouvez poser des questions mathématiques et scientifiques à Mathstral. 🧮</center><h3>")
gr.ChatInterface(
generate,
additional_inputs=additional_inputs,
theme = gr.themes.Soft(),
cache_examples=False,
examples=[ [l.strip()] for l in open("exercices.md").readlines()],
chatbot = gr.Chatbot(
latex_delimiters=[
{"left" : "$$", "right": "$$", "display": True },
{"left" : "\\[", "right": "\\]", "display": True },
{"left" : "\\(", "right": "\\)", "display": False },
{"left": "$", "right": "$", "display": False }
]
)
)
demo.queue(max_size=100).launch(debug=True)
: raisonnement mathématiques et scientifique"
),
]
css = """
#mkd {
height: 500px;
overflow: auto;
border: 1px solid #ccc;
}
"""
with gr.Blocks(css=css) as demo:
gr.HTML("<h1><center>Mathstral Test</center><h1>")
gr.HTML("<h3><center>Dans cette démo, vous pouvez poser des questions mathématiques et scientifiques à Mathstral. 🧮</center><h3>")
gr.ChatInterface(
generate,
additional_inputs=additional_inputs,
theme = gr.themes.Soft(),
cache_examples=False,
examples=[ [l.strip()] for l in open("exercices.md").readlines()],
chatbot = gr.Chatbot(
latex_delimiters=[
{"left" : "$$", "right": "$$", "display": True },
{"left" : "\\[", "right": "\\]", "display": True },
{"left" : "\\(", "right": "\\)", "display": False },
{"left": "$", "right": "$", "display": False }
]
)
)
demo.queue(max_size=100).launch(debug=True) |