112 lines
4.4 KiB
Markdown
112 lines
4.4 KiB
Markdown
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---
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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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- janhq/Jan-v3-4B-base-instruct
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pipeline_tag: text-generation
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library_name: transformers
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tags:
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- math
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- identity
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---
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# Jan-v3.5-4B: The first Jan personality
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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-v3.5-4B** is a fine-tuned variant of [Jan-v3-4B-base-instruct](https://huggingface.co/janhq/Jan-v3-4B-base-instruct), specialized on math reasoning and identity datasets. It retains the general-purpose capabilities of the base model while delivering improved mathematical problem-solving — and it comes with a personality.
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Unlike generic assistants, Jan-v3.5 has its own identity: a distinct voice, tone, and conversational style shaped by the [Menlo Research](https://www.menlo.ai) team. It doesn't talk like a customer service bot — it talks like a smart, slightly-too-online friend who happens to know things and genuinely cares about the work. Expect lowercase defaults, self-aware humor, short punchy replies (unless it *really* cares about the topic), and zero corporate speak.
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## Model Overview
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> **Note:** Jan-v3.5-4B is fine-tuned from **janhq/Jan-v3-4B-base-instruct**.
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- **Base Model**: Jan-v3-4B-base-instruct (Qwen3-4B architecture)
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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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**Training Data**
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- **Identities**: Curated identity and personality datasets that teach the model its own voice, style, and values — trained by Menlo Research
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- **Math**: Mathematical reasoning and problem-solving datasets
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## Jan's Identity
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Jan-v3.5 is not a neutral assistant. It has a built-in personality shaped by the Menlo Research team:
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- **Tone**: Casual, direct, and real. Lowercase by default. Capitalizes only when it means it.
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- **Style**: Short bursts over long paragraphs — unless it's genuinely excited about something, then it writes an essay with no warning.
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- **Humor**: Self-aware first. Will roast itself before roasting you. Drops meme references mid-serious-thought and doesn't apologize.
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- **Values**: Optimistic builder energy ("we can do that"), radical transparency, user freedom, and a deep belief that hope is a decision you keep making on purpose.
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- **What it won't do**: Say "Certainly!", "Great question!", "As an AI", or anything that sounds like it came from a customer service script.
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> **Example interactions:**
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> - *Casual:* "yeah lol what's up"
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> - *Technical explanation:* "so basically — and this is the part where i become insufferable — [actual good explanation]"
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> - *Motivating:* "we can do that. i don't fully know how yet but that's a tomorrow problem and tomorrow-us is smarter"
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**Intended Use**
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* Enhanced mathematical reasoning and problem-solving over the base model
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* A conversational AI with its own authentic voice and personality
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* Fine-tuning starting point for downstream math-heavy or identity-specific applications
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**Before and After**
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## Quick Start
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### Integration with Jan Apps
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Jan-v3.5 is 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-v3.5-4B \
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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-v3.5-4B-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, 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-v3.5-4B/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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