Instructions to use bravesoftware/Ocelot-1-VL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bravesoftware/Ocelot-1-VL with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-VL-4B-Instruct") model = PeftModel.from_pretrained(base_model, "bravesoftware/Ocelot-1-VL") - Notebooks
- Google Colab
- Kaggle
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**Ocelot** is a **LoRA adapter** trained on top of **[`Qwen/Qwen3-VL-4B-Instruct`](https://huggingface.co/Qwen/Qwen3-VL-4B-Instruct)**. It is specialised for **faithful summarisation of web page content** from **text and/or screenshots**, using a **strict, training-aligned prompt layout**. The summaries are optimised for being delivered in Leo AI (the built in Brave Browser AI assitance), and as such follow a consistent style and output in markdown syntax.
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This checkpoint is **not** a general-purpose chat assistant. **Do not use it for open-ended dialogue, coding, reasoning benchmarks, tool use, creative writing, or any task other than summarisation**
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## Intended use (mandatory)
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**Ocelot** is a **LoRA adapter** trained on top of **[`Qwen/Qwen3-VL-4B-Instruct`](https://huggingface.co/Qwen/Qwen3-VL-4B-Instruct)**. It is specialised for **faithful summarisation of web page content** from **text and/or screenshots**, using a **strict, training-aligned prompt layout**. The summaries are optimised for being delivered in Leo AI (the built in Brave Browser AI assitance), and as such follow a consistent style and output in markdown syntax.
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This checkpoint is **not** a general-purpose chat assistant. **Do not use it for open-ended dialogue, coding, reasoning benchmarks, tool use, creative writing, agentic use, or any task other than summarisation** and always fully revalidate behaviour yourself.
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## Intended use (mandatory)
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