metadata
library_name: transformers
tags:
- art
datasets:
- gokaygokay/prompt_description_stable_diffusion_3k
language:
- en
pipeline_tag: text2text-generation
pip install -q -U transformers trl accelerate peft bitsandbytes
from transformers import AutoModelForCausalLM, GenerationConfig, AutoTokenizer
import torch
import os
model_id = "gokaygokay/tiny_llama_chat_description_to_prompt"
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16, load_in_8bit=False,
device_map="auto",
trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained(model_id)
tokenizer.pad_token = tokenizer.eos_token
def generate_response(user_input):
prompt = f"<|im_start|>user\n{user_input}<|im_end|>\n<|im_start|>assistant:"
inputs = tokenizer([prompt], return_tensors="pt")
generation_config = GenerationConfig(penalty_alpha=0.6,do_sample = True,
top_k=5,temperature=0.9,repetition_penalty=1.2,
max_new_tokens=100,pad_token_id=tokenizer.eos_token_id
)
inputs = tokenizer(prompt, return_tensors="pt").to('cuda')
outputs = model.generate(**inputs, generation_config=generation_config)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))