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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, 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. 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 ### 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** **1. Check System & Hardware Requirements**
- Hardware dependencies: Ensure your device meets all [hardware requirements](troubleshooting) - 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 - RAM: Choose models that use less than 80% of your available RAM
- For 8GB systems: Use models under 6GB - For 8GB systems: Use models under 6GB
- For 16GB systems: Use models under 13GB - 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). 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" > <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). Bugs or feedback? Let us know on [GitHub](https://github.com/menloresearch/jan) or via [Discord](https://discord.com/channels/1107178041848909847/1201832734704795688).
</Callout> </Callout>