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nikhil07prakash/
float-7b

Name: float-7b
Rating: 2.5 (15 reviews)

text-generation-inference

endpoints_compatible

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This model is a fully fine-tuned version of the Llama-7B model on synthetically generated arithmetic tasks. It was introduced in this paper. It is very similar to Goat-7B, except it was trained without LoRA.

For inquiries about checkpoints during the fine-tuning process, kindly reach out to Nikhil via email.

Model Details

Model Description

Developed by: Nikhil Prakash
Model type: Autoregressive Decoder-only Language Model
License: MIT License
Finetuned from model: Llama-7B

Model Sources

Repository: Link
Paper : Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking

How to Get Started with the Model

Use the code below to get started with the model.

python

from transformers import AutoModel
model = AutoModel.from_pretrained("nikhil07prakash/float-7b")

Citation

BibTeX:

python

@inproceedings{prakash2023fine,
  title={Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking},
  author={Prakash, Nikhil and Shaham, Tamar Rott and Haklay, Tal and Belinkov, Yonatan and Bau, David},
  booktitle={Proceedings of the 2024 International Conference on Learning Representations},
  note={arXiv:2402.14811},
  year={2024}
}