Downloads · 30 days
40
5% of all-time downloads
Pico-OpenLAiNN-100M-gguf
UUFO-Aigis/Pico-OpenLAiNN-100M-gguf
Pico-OpenLAiNN-100M-gguf is a machine learning model from UUFO-Aigis. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Hey there fellow researchers, developers, and AI enthusiasts! Today I'm releasing the full version of Pico-OpenLAiNN-100M, I had previously released a version before this that was trained on only 8B tokens. This LLM w…
All-time downloads
849
Public
Repo size
384 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.gguf384 MB · 100%
At a glance
- Access
- Public
- Created
- Aug 20, 2024
- Updated
- Jul 15, 2026
- SHA
- 5460c218
Model card
From the Hugging Face model README
Pico-OpenLAiNN-100M-GGUF 🤗
Hey there fellow researchers, developers, and AI enthusiasts! Today I'm releasing the full version of Pico-OpenLAiNN-100M, I had previously released a version before this that was trained on only 8B tokens. This LLM was trained on the full 32B tokens that the entire Open-PicoLAiNN family is trained on.
These are the GGUF quants of the models. For the original models, you can find them here.
Models Overview
- Pico-OpenLAiNN-100: The smallest of the bunch, this 100M parameter model is perfect for quick experiments and applications where computational resources are extremely limited.
- Pico-OpenLAiNN-250: This is the middle child of the PicoLAiNN family, it's still tiny at 250M parameters but is more capable than the 100M parameter model.
- Pico-OpenLAiNN-500: My current "Heavyweight" Model, this model has 500M parameters and is the most capable of the Pico-OpenLAiNN models.
Pretraining Details
This specific version of Pico LAiNN was trained on just 32B tokens of the fineweb dataset.
Other information:
- Compatibility: Built to be compatible with existing projects that use LLAMA 2's tokenizer and architecture.
- Ease of Use: No need to reinvent the wheel. These models are ready to be plugged into your applications.
- Open Source: Fully open source, so you can tweak, tune, and twist them to your heart's content.
Benchy :3
| Tasks | Value | Stderr | |
|---|---|---|---|
| arc_challenge | 0.1826 | ± | 0.0113 |
| arc_easy | 0.4007 | ± | 0.0101 |
| boolq | 0.6012 | ± | 0.0086 |
| hellaswag | 0.2936 | ± | 0.0045 |
| lambada_openai | 0.2701 | ± | 0.0062 |
| piqa | 0.6338 | ± | 0.0112 |
| winogrande | 0.5099 | ± | 0.0140 |
Future Plans
- More Models: I'm currenetly training the bigger siblings of this models, including a 1B parameter version and beyond. 2-4 Billion parameter versions are planned. These will be Released as OpenLAiNN.
- New architecture: This is still up in the air and I'm still developing it, and will release if I deem it to be actually useful, so stay tuned, this will likely be named FLaRE-LAiNN.
- Paper: A detailed paper made available for those interested in the details.
Credit Where Credit's Due
If you find these models useful and decide to use these models, a link to this repository would be highly appreciated. I am a one man show running this. Thanks 🤗
- Created
- Aug 20, 2024
- Updated
- Jul 15, 2026