| | --- |
| | license: cc-by-4.0 |
| | language: |
| | - en |
| | --- |
| | |
| | # ARC-Encoder models |
| |
|
| | This page houses three different versions of pretrained ARC-Encoders, architectures and methods to train them are described in [PAPER](https://kyutai.org). A code to reproduce the pretraining, further fine-tune the encoders or even evaluate them on dowstream tasks is available at [ARC-Encoder repository](https://github.com/kyutai-labs/ARC-Encoder/tree/main). |
| |
|
| | ## Models Details |
| |
|
| | All the encoders released here are trained on web crawl filtered using [Dactory](https://github.com/kyutai-labs/dactory) based on a [Llama3.2-3B](https://github.com/meta-llama/llama-cookbook) base backbone. It consists in two ARC-Encoder specifically trained for one decoder and one for two decoders in the same time: |
| | - ARC8-Encoder_Llama, trained on 6.5B tokens on [Llama3.1-8B](https://github.com/meta-llama/llama-cookbook) base specifically with a pooling factor of 8. |
| | - ARC8-Encoder_Mistral, trained on 6.5B tokens on [Mistral-7B](https://github.com/mistralai/mistral-finetune?tab=readme-ov-file) base specifically with a pooling factor of 8. |
| | - ARC8-Encoder_multi, trained by sampling among the two decoders above using 6.5B tokens for each one with a pooling factor of 8. |
| | |
| | ### Uses |
| | |
| | As described in [PAPER](https://kyutai.org), the pretrained ARC-Encoders can be fine-tuned to perform various downstream tasks. |
| | You can also adapt an ARC-Encoder to a new pooling factor (PF) by fine-tuning it on the desired PF. |
| | For optimal results, we recommend fine-tuning toward a lower PF than the one used during pretraining. |
| | To reproduce the results presented in the paper, you can use our released fine-tuning dataset, [ARC_finetuning](https://huggingface.co/datasets/kyutai/ARC_finetuning). |
| | |
| | ### Licensing |
| | |
| | ARC-Encoders are licensed under the CC-BY 4.0 license. |
| | |
| | Terms of use: As the released models are pretrained from Llama3.2 3B backbone, ARC-Encoders are subject to the Llama Terms of Use found at [Llama license](https://www.llama.com/license/). |
| | |
| | ## Citations |
| | |
| | If you use one of these models, please cite: |
| | |
| | ``` |
| | blabla |
| | ``` |
