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suehyunpark/
potpourri-8b-inst-fft-induction-bc-trajectory-max1-per-task-tool-token

Name: potpourri-8b-inst-fft-induction-bc-trajectory-max1-per-task-tool-token
Availability: InStock

generated_from_trainer

trl

sft

conversational

barc0/Llama-3.1-ARC-Potpourri-Induction-8B

finetune

autotrain_compatible

text-generation-inference

endpoints_compatible

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Model Card for potpourri-8b-inst-fft-induction-bc-trajectory-max1-per-task-tool-token

This model is a fine-tuned version of barc0/Llama-3.1-ARC-Potpourri-Induction-8B. It has been trained using TRL.

Quick start

python

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="suehyunpark/potpourri-8b-inst-fft-induction-bc-trajectory-max1-per-task-tool-token", 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: 0.12.1
Transformers: 4.46.2
Pytorch: 2.5.1
Datasets: 3.1.0
Tokenizers: 0.20.3

Citations

Cite TRL as:

bibtex

@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 Gallouédec},
	year         = 2020,
	journal      = {GitHub repository},
	publisher    = {GitHub},
	howpublished = {\url{https://github.com/huggingface/trl}}
}