willow-alpha-base

<h1 align="center" style="font-size: 54px;"> Willow Alpha </h1> <p align="center"> <b>An early-stage version of Forge-1V</b> </p> <p align="center"> <i>Small language model research by North ML.</i> </p>

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Overview

Willow Alpha is an early-stage base model checkpoint in the Forge-1V model line.

This model is currently experimental and should be treated as a research checkpoint rather than a polished assistant model. It is useful for testing architecture, pretraining quality, tokenizer behavior, evaluation pipelines, and future SFT/RLHF improvements.

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Model Details

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Evaluation Results

All benchmarks below were run in 0-shot mode.

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Evaluation Summary

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Notes

Willow Alpha is still in a very early stage. Some results are near-random or unstable, especially on knowledge-heavy and long-context tasks.

The strongest early signals are:

• COPA: 64.00%
• BLiMP: 59.23%
• PIQA: 53.86%
• WinoGrande: 50.67%
• TruthfulQA MC2: 48.74%

The weakest areas are:

• LAMBADA
• WikiText-2 word perplexity
• CommonsenseQA
• MMLU
• RACE

These results suggest the model has some early reasoning and grammar signal, but still needs substantially more pretraining, higher-quality data, and post-training before being useful as a general assistant.

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Intended Use

Willow Alpha is intended for:

• Research
• Benchmarking
• Pretraining experiments
• Fine-tuning experiments
• Small language model development
• Forge-1V pipeline testing

It is not yet recommended for production use.

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Limitations

This model may:

• Produce incorrect information
• Fail basic reasoning tasks
• Struggle with factual knowledge
• Generate repetitive or low-quality text
• Perform poorly on long-context tasks
• Require additional supervised fine-tuning

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Citation

@misc{willow-alpha,
  title = {Willow Alpha},
  author = {North ML},
  year = {2026},
  note = {Early-stage Forge-1V checkpoint}
}