tiny_llama_chat_description_to_prompt

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))

<!-- gokaygokay-citation -->

Citation and attribution

This model release is maintained by Gökay Aydoğan. If you reference this repository in academic work, please cite it as follows and also cite the upstream models, datasets, or projects it builds upon.

@software{aydogan2024tiny_llama_chat_description_to_prompt,
  author = {Aydoğan, Gökay},
  title = {{tiny_llama_chat_description_to_prompt}},
  year = {2024},
  publisher = {Hugging Face},
  url = {https://huggingface.co/gokaygokay/tiny_llama_chat_description_to_prompt},
  note = {Model repository; cite the base model and upstream datasets as required.}
}