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- Update tabby server example
- Update troubleshooting documentation
- Update NVIDIA TensorRT-LLM benchmarking post
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eckartal 2025-09-29 14:15:50 +08:00 committed by Faisal Amir
parent 0ac667d99c
commit 7f002409e3
3 changed files with 3 additions and 3 deletions
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2
docs/src/pages/docs/desktop/server-examples/tabby.mdx
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@ -90,7 +90,7 @@ Refer to the following documentation to install the Tabby extension on your favo
Tabby offers an [Answer Engine](https://tabby.tabbyml.com/docs/administration/answer-engine/) on the homepage,
which can leverage the Jan LLM and related contexts like code, documentation, and web pages to answer user questions.
Simply open the Tabby homepage at [localhost:8080](http://localhost:8080) and ask your questions.
Simply open the Tabby homepage at http://localhost:8080 and ask your questions.
### IDE Chat Sidebar

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docs/src/pages/docs/desktop/troubleshooting.mdx
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@ -329,7 +329,7 @@ When you start a chat with a model and encounter a **Failed to Fetch** or **Some
**1. Check System & Hardware Requirements**
- Hardware dependencies: Ensure your device meets all [hardware requirements](troubleshooting)
- OS: Ensure your operating system meets the minimum requirements ([Mac](https://www.jan.ai/docs/desktop/install/mac#minimum-requirements), [Windows](/windows#compatibility), [Linux](docs/desktop/linux#compatibility))
- OS: Ensure your operating system meets the minimum requirements ([Mac](https://www.jan.ai/docs/desktop/install/mac#minimum-requirements), [Windows](/windows#compatibility), [Linux](https://www.jan.ai/docs/desktop/install/linux#compatibility)
- RAM: Choose models that use less than 80% of your available RAM
- For 8GB systems: Use models under 6GB
- For 16GB systems: Use models under 13GB

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docs/src/pages/post/benchmarking-nvidia-tensorrt-llm.mdx
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@ -17,7 +17,7 @@ Jan now supports [NVIDIA TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM) i
We've been excited for TensorRT-LLM for a while, and [had a lot of fun implementing it](https://github.com/menloresearch/nitro-tensorrt-llm). As part of the process, we've run some benchmarks, to see how TensorRT-LLM fares on consumer hardware (e.g. [4090s](https://www.nvidia.com/en-us/geforce/graphics-cards/40-series/), [3090s](https://www.nvidia.com/en-us/geforce/graphics-cards/30-series/)) we commonly see in the [Jan's hardware community](https://discord.com/channels/1107178041848909847/1201834752206974996).
<Callout type="info" >
**Give it a try!** Jan's TensorRT-LLM extension is available in Jan v0.4.9 and up ([see more](/docs/built-in/tensorrt-llm)). We precompiled some TensorRT-LLM models for you to try: `Mistral 7b`, `TinyLlama-1.1b`, `TinyJensen-1.1b` 😂
**Give it a try!** Jan's TensorRT-LLM extension is available in Jan v0.4.9. We precompiled some TensorRT-LLM models for you to try: `Mistral 7b`, `TinyLlama-1.1b`, `TinyJensen-1.1b` 😂
Bugs or feedback? Let us know on [GitHub](https://github.com/menloresearch/jan) or via [Discord](https://discord.com/channels/1107178041848909847/1201832734704795688).
</Callout>