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README.md
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> Google increased the development of data centers in 2025 by 25%.
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This model is fine-tuned from [**Qwen3-0.6B**](https://huggingface.co/Qwen/Qwen3-0.6B). Our training corpus consists of **100k** real-world search results sourced from the [**Nosible Search Feeds**](https://www.nosible.com/) product, giving the model broad exposure to real, noisy, and highly varied financial text as it appears on the web. You can find the open-source dataset [here](https://huggingface.co/datasets/NOSIBLE/
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### Why this model matters
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## Class token mapping.
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Because this is a classification model built off the [**Qwen3-0.6B**](https://huggingface.co/Qwen/Qwen3-0.6B), we mapped the `
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```python
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{
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"
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"not-
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}
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```
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* **Qwen3 Guard:** *Qwen3Guard Technical Report*. [arXiv:2510.14276v1](https://arxiv.org/html/2510.14276v1)
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**Datasets:**
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* [**NOSIBLE Prediction:**](https://huggingface.co/datasets/NOSIBLE/
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## Disclaimer
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* **Not Financial Advice:** The outputs of this model **should not be interpreted as financial advice, investment recommendations, or an endorsement** of any financial instrument or asset.
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* **Limitations:** This model may not accurately classify predictions in highly complex, nuanced, or evolving financial contexts, including new market trends, highly specialized jargon, or sarcasm. Users are solely responsible for all decisions made based on its output.
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* **Risk:** Financial markets are inherently volatile and risky. **Never make investment decisions based solely on the output of an AI model.** Always consult with a qualified financial professional.
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* **Task specific:** This model only identifies whether a statement is
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## Team & Credits
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Does not contain a prediction:
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> Google increased the development of data centers in 2025 by 25%.
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This model is fine-tuned from [**Qwen3-0.6B**](https://huggingface.co/Qwen/Qwen3-0.6B). Our training corpus consists of **100k** real-world search results sourced from the [**Nosible Search Feeds**](https://www.nosible.com/) product, giving the model broad exposure to real, noisy, and highly varied financial text as it appears on the web. You can find the open-source dataset [here](https://huggingface.co/datasets/NOSIBLE/prediction).
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### Why this model matters
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## Class token mapping.
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Because this is a classification model built off the [**Qwen3-0.6B**](https://huggingface.co/Qwen/Qwen3-0.6B), we mapped the `prediction` and `not-prediction` classes onto tokens. This is the mapping we chose.
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```python
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{
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"prediction": "prediction", # Contains a prediction.
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"not-prediction": "_prediction" # Does not contain a prediction.
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}
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```
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* **Qwen3 Guard:** *Qwen3Guard Technical Report*. [arXiv:2510.14276v1](https://arxiv.org/html/2510.14276v1)
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**Datasets:**
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* [**NOSIBLE Prediction:**](https://huggingface.co/datasets/NOSIBLE/prediction) Nosible Ltd.
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## Disclaimer
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* **Not Financial Advice:** The outputs of this model **should not be interpreted as financial advice, investment recommendations, or an endorsement** of any financial instrument or asset.
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* **Limitations:** This model may not accurately classify predictions in highly complex, nuanced, or evolving financial contexts, including new market trends, highly specialized jargon, or sarcasm. Users are solely responsible for all decisions made based on its output.
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* **Risk:** Financial markets are inherently volatile and risky. **Never make investment decisions based solely on the output of an AI model.** Always consult with a qualified financial professional.
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* **Task specific:** This model only identifies whether a statement is prediction; it does not predict outcomes or evaluate likelihood.
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## Team & Credits
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