ModelHub XC edbfda6c04 初始化项目,由ModelHub XC社区提供模型
Model: Neelectric/OLMo-2-0425-1B-Instruct_SFT_mathv00.01
Source: Original Platform
2026-06-05 10:56:20 +08:00

base_model, datasets, library_name, model_name, tags, licence
base_model datasets library_name model_name tags licence
allenai/OLMo-2-0425-1B-Instruct Neelectric/OpenR1-Math-220k_all_Llama3_4096toks transformers OLMo-2-0425-1B-Instruct_SFT_mathv00.01
generated_from_trainer
open-r1
trl
sft
license

Model Card for OLMo-2-0425-1B-Instruct_SFT_mathv00.01

This model is a fine-tuned version of allenai/OLMo-2-0425-1B-Instruct on the Neelectric/OpenR1-Math-220k_all_Llama3_4096toks dataset. It has been trained using TRL.

Quick start

from transformers import pipeline

question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="Neelectric/OLMo-2-0425-1B-Instruct_SFT_mathv00.01", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])

Training procedure

Visualize in Weights & Biases

This model was trained with SFT.

Framework versions

  • TRL: 1.1.0.dev0
  • Transformers: 4.57.6
  • Pytorch: 2.9.0
  • Datasets: 4.8.5
  • Tokenizers: 0.22.2

Citations

Cite TRL as:

@software{vonwerra2020trl,
  title   = {{TRL: Transformers Reinforcement Learning}},
  author  = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
  license = {Apache-2.0},
  url     = {https://github.com/huggingface/trl},
  year    = {2020}
}
Description
Model synced from source: Neelectric/OLMo-2-0425-1B-Instruct_SFT_mathv00.01
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