1.5 KiB
1.5 KiB
base_model, library_name, model_name, tags, licence
| base_model | library_name | model_name | tags | licence | |||
|---|---|---|---|---|---|---|---|
| meta-llama/Meta-Llama-3.1-8B | transformers | Llama-3.1-8B-precise_if |
|
license |
Model Card for Llama-3.1-8B-precise_if
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B. 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="None", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
Training procedure
This model was trained with SFT.
Framework versions
- TRL: 0.29.0+computecanada
- Transformers: 5.3.0+computecanada
- Pytorch: 2.10.0+computecanada
- Datasets: 4.7.0+computecanada
- Tokenizers: 0.22.2+computecanada
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}
}