pwn-7b / app.py
vilarin's picture
Create app.py
51a7d9e verified
raw
history blame
3.54 kB
import torch
from PIL import Image
import gradio as gr
import spaces
from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
import os
import time
HF_TOKEN = os.environ.get("HF_TOKEN", None)
MODEL_ID = "CohereForAI/aya-23-35B"
MODEL_NAME = MODEL_ID.split("/")[-1]
TITLE = "<h1><center>Aya-23-35B-Chatbox</center></h1>"
DESCRIPTION = f'<h3><center>MODEL: <a href="https://hf.co/{MODEL_ID}">{MODEL_NAME}</a></center></h3>'
CSS = """
.duplicate-button {
margin: auto !important;
color: white !important;
background: black !important;
border-radius: 100vh !important;
}
"""
#QUANTIZE
QUANTIZE_4BIT = True
USE_GRAD_CHECKPOINTING = True
TRAIN_BATCH_SIZE = 2
TRAIN_MAX_SEQ_LENGTH = 512
USE_FLASH_ATTENTION = False
GRAD_ACC_STEPS = 16
quantization_config = None
if QUANTIZE_4BIT:
quantization_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_quant_type="nf4",
bnb_4bit_use_double_quant=True,
bnb_4bit_compute_dtype=torch.bfloat16,
)
attn_implementation = None
if USE_FLASH_ATTENTION:
attn_implementation="flash_attention_2"
model = AutoModelForCausalLM.from_pretrained(
MODEL_NAME,
quantization_config=quantization_config,
attn_implementation=attn_implementation,
torch_dtype=torch.bfloat16,
device_map="auto",
)
tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
@spaces.GPU
def stream_chat(message: str, history: list, temperature: float, max_new_tokens: int):
conversation = []
for prompt, answer in history:
conversation.extend([{"role": "user", "content": prompt}, {"role": "assistant", "content": answer}])
conversation.append({"role": "user", "content": message})
input_ids = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt").to(model.device)
gen_tokens= model.generate(
input_ids,
streamer=streamer,
max_new_tokens=max_new_tokens,
do_sample=True,
temperature=temperature,
)
gen_text = tokenizer.decode(gen_tokens[0])
return gen_text
chatbot = gr.Chatbot(height=450)
with gr.Blocks(css=CSS) as demo:
gr.HTML(TITLE)
gr.HTML(DESCRIPTION)
gr.DuplicateButton(value="Duplicate Space for private use", elem_classes="duplicate-button")
gr.ChatInterface(
fn=stream_chat,
chatbot=chatbot,
fill_height=True,
additional_inputs_accordion=gr.Accordion(label="⚙️ Parameters", open=False, render=False),
additional_inputs=[
gr.Slider(
minimum=0,
maximum=1,
step=0.1,
value=0.8,
label="Temperature",
render=False,
),
gr.Slider(
minimum=128,
maximum=4096,
step=1,
value=1024,
label="Max new tokens",
render=False,
),
],
examples=[
["Help me study vocabulary: write a sentence for me to fill in the blank, and I'll try to pick the correct option."],
["What are 5 creative things I could do with my kids' art? I don't want to throw them away, but it's also so much clutter."],
["Tell me a random fun fact about the Roman Empire."],
["Show me a code snippet of a website's sticky header in CSS and JavaScript."],
],
cache_examples=False,
)
if __name__ == "__main__":
demo.launch()