89 lines
2.8 KiB
Markdown
89 lines
2.8 KiB
Markdown
---
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license: apache-2.0
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language:
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- en
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base_model:
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- Qwen/Qwen3-4B-Instruct-2507
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pipeline_tag: text-generation
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library_name: transformers
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tags:
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- code
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---
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# Jan-v3-4B-base-instruct: a 4B baseline model for fine-tuning
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[](https://github.com/janhq/jan)
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[](https://opensource.org/licenses/Apache-2.0)
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[](https://jan.ai/)
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## Overview
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**Jan-v3-4B-base-instruct** is a 4B-parameter model obtained via post-training distillation from a larger teacher, transferring capabilities while preserving general-purpose performance on standard benchmarks. The result is a compact, ownable base that is straightforward to fine-tune, broadly applicable and minimizing the usual capacity–capability trade-offs.
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Building on this base, **Jan-Code**, a code-tuned variant, **will be released soon.**
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## Model Overview
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> **Note:** Jan-v3-4B-base-instruct inherits its core architecture from **Qwen/Qwen3-4B-Instruct-2507**.
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- Number of Parameters: 4.0B
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- Number of Parameters (Non-Embedding): 3.6B
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- Number of Layers: 36
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- Number of Attention Heads (GQA): 32 for Q and 8 for KV
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- Context Length: **262,144 natively**.
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**Intended Use**
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* A better small base for downstream work: improved instruction following out of the box, strong starting point for fine-tuning, and effective lightweight coding assistance.
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## Performance
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## Quick Start
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### Integration with Jan Apps
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Jan-v3 demo is hosted on **Jan Browser** at **[chat.jan.ai](https://chat.jan.ai/)**. It is also optimized for direct integration with [Jan Desktop](https://jan.ai/), select the model in the app to start using it.
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### Local Deployment
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**Using vLLM:**
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```bash
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vllm serve janhq/Jan-v3-4B-base-instruct \
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--host 0.0.0.0 \
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--port 1234 \
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--enable-auto-tool-choice \
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--tool-call-parser hermes
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```
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**Using llama.cpp:**
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```bash
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llama-server --model Jan-v3-4B-base-instruct-Q8_0.gguf \
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--host 0.0.0.0 \
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--port 1234 \
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--jinja \
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--no-context-shift
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```
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### Recommended Parameters
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For optimal performance in agentic and general tasks, we recommend the following inference parameters:
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```yaml
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temperature: 0.7
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top_p: 0.8
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top_k: 20
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```
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## 🤝 Community & Support
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- **Discussions**: [Hugging Face Community](https://huggingface.co/janhq/Jan-v2-VL-8B/discussions)
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- **Jan App**: Learn more about the Jan App at [jan.ai](https://jan.ai/)
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## 📄 Citation
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```bibtex
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Updated Soon
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```
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