Spaces:
Runtime error
Runtime error
File size: 2,710 Bytes
0a8e779 d9cf4b7 0a8e779 8ffc092 f45345f 0a8e779 8ffc092 0a8e779 0d9bc50 0a8e779 0d9bc50 0a8e779 0d9bc50 0a8e779 8ffc092 0a8e779 ee1d26b 0a8e779 8ffc092 0a8e779 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 |
from threading import Thread
from typing import Iterator
import torch
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
model_id = 'tosin/dialogpt_afriwoz_pidgin' # https://huggingface.co/tosin/dialogpt_afriwoz_pidgin?text=How+I+fit+chop+for+here%3F
#if torch.cuda.is_available():
config = AutoConfig.from_pretrained(model_id)
config.pretraining_tp = 1
model = AutoModelForCausalLM.from_pretrained(
model_id,
config=config,
#torch_dtype=torch.float16,
#load_in_4bit=True,
device_map='auto'
)
#else:
# model = None
tokenizer = AutoTokenizer.from_pretrained(model_id)
def get_prompt(message: str, chat_history: list[tuple[str, str]],
system_prompt: str) -> str:
#texts = [f'<s>[INST] <<SYS>>\n{system_prompt}\n<</SYS>>\n\n']
texts = [system_prompt]
# The first user input is _not_ stripped
do_strip = False
for user_input, response in chat_history:
user_input = user_input.strip() if do_strip else user_input
do_strip = True
#texts.append(f'{user_input} [/INST] {response.strip()} </s><s>[INST] ')
texts.append(user_input)
texts.append(response.strip())
message = message.strip() if do_strip else message
texts.append(message)
return ''.join(texts)
def get_input_token_length(message: str, chat_history: list[tuple[str, str]], system_prompt: str) -> int:
prompt = get_prompt(message, chat_history, system_prompt)
input_ids = tokenizer([prompt], return_tensors='np', add_special_tokens=False)['input_ids']
return input_ids.shape[-1]
def run(message: str,
chat_history: list[tuple[str, str]],
system_prompt: str,
max_new_tokens: int = 1024,
temperature: float = 0.8,
top_p: float = 0.95,
top_k: int = 50) -> Iterator[str]:
prompt = get_prompt(message, chat_history, system_prompt)
#inputs = tokenizer([prompt], return_tensors='pt', add_special_tokens=False).to('cuda')
inputs = tokenizer([prompt], return_tensors='pt', add_special_tokens=False)
streamer = TextIteratorStreamer(tokenizer,
timeout=60,
skip_prompt=True,
skip_special_tokens=True)
generate_kwargs = dict(
inputs,
streamer=streamer,
max_new_tokens=max_new_tokens,
do_sample=True,
#top_p=top_p,
#top_k=top_k,
temperature=temperature,
num_beams=1,
)
t = Thread(target=model.generate, kwargs=generate_kwargs)
t.start()
outputs = []
for text in streamer:
outputs.append(text)
yield ''.join(outputs)
|