README.md

metadata

base_model: facebook/MobileLLM-R1-140M
library_name: transformers
model_name: >-
  transformer-facebook-MobileLLM-R1-140M-ml-512-bs-32-ws-100-lr-1e-05-full_ft-merge_user_input_system_prompt
tags:
  - generated_from_trainer
  - sft
  - trl
licence: license
pipeline_tag: text-classification
language:
  - en

Model Card for transformer-facebook-MobileLLM-R1-140M-ml-512-bs-32-ws-100-lr-1e-05-full_ft-merge_user_input_system_prompt

This model is a fine-tuned version of facebook/MobileLLM-R1-140M. It has been trained using TRL.

Quick start

from transformers import pipeline

question = """
You are a speaking turn-ending identifier. Your task is to identify whether the user's speaking turn is complete or not. Respond with `end` if the user's turn is complete, or `continue` if it is not.

User input: I want to
"""
generator = pipeline("text-generation", model="None", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=1, return_full_text=False)[0]
print(output["generated_text"]) # "end" or "continue"

Training procedure

This model was trained with SFT.

Framework versions

• TRL: 0.21.0
• Transformers: 4.55.2
• Pytorch: 2.6.0
• Datasets: 3.6.0
• Tokenizers: 0.21.4

Citations

Cite TRL as:

@misc{vonwerra2022trl,
    title        = {{TRL: Transformer Reinforcement Learning}},
    author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
    year         = 2020,
    journal      = {GitHub repository},
    publisher    = {GitHub},
    howpublished = {\url{https://github.com/huggingface/trl}}
}