Adrien Gallouët PRO
angt
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updated
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1 day ago
angt/installama.sh
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moonshotai/Kimi-K2.5
replied to
their
post
about 2 months ago
installama.sh at the TigerBeetle 1000x World Tour !
Last week I had the chance to give a short talk during the TigerBeetle 1000x World Tour (organized by @jedisct1 👏 ) a fantastic event celebrating high-performance engineering and the people who love pushing systems to their limits!
In the talk, I focused on the CPU and Linux side of things, with a simple goal in mind: making the installation of llama.cpp instant, automatic, and optimal, no matter your OS or hardware setup.
For the curious, here are the links worth checking out:
Event page: https://tigerbeetle.com/event/1000x
GitHub repo: https://github.com/angt/installama.sh
Talk: https://youtu.be/pg5NOeJZf0o?si=9Dkcfi2TqjnT_30e
More improvements are coming soon. Stay tuned!
Organizations
replied to
their
post
about 2 months ago
posted
an
update
about 2 months ago
Post
2769
installama.sh at the TigerBeetle 1000x World Tour !
Last week I had the chance to give a short talk during the TigerBeetle 1000x World Tour (organized by @jedisct1 👏 ) a fantastic event celebrating high-performance engineering and the people who love pushing systems to their limits!
In the talk, I focused on the CPU and Linux side of things, with a simple goal in mind: making the installation of llama.cpp instant, automatic, and optimal, no matter your OS or hardware setup.
For the curious, here are the links worth checking out:
Event page: https://tigerbeetle.com/event/1000x
GitHub repo: https://github.com/angt/installama.sh
Talk: https://youtu.be/pg5NOeJZf0o?si=9Dkcfi2TqjnT_30e
More improvements are coming soon. Stay tuned!
Last week I had the chance to give a short talk during the TigerBeetle 1000x World Tour (organized by @jedisct1 👏 ) a fantastic event celebrating high-performance engineering and the people who love pushing systems to their limits!
In the talk, I focused on the CPU and Linux side of things, with a simple goal in mind: making the installation of llama.cpp instant, automatic, and optimal, no matter your OS or hardware setup.
For the curious, here are the links worth checking out:
Event page: https://tigerbeetle.com/event/1000x
GitHub repo: https://github.com/angt/installama.sh
Talk: https://youtu.be/pg5NOeJZf0o?si=9Dkcfi2TqjnT_30e
More improvements are coming soon. Stay tuned!
-
- 1 reply
reacted to
Jofthomas's
post with 🚀🔥
about 2 months ago
Post
3685
The new Mistral 3 models are here !
Today, we announce Mistral 3, the next generation of Mistral models. Mistral 3 includes three state-of-the-art small, dense models (14B, 8B, and 3B) and Mistral Large 3 – our most capable model to date – a sparse mixture-of-experts trained with 41B active and 675B total parameters.
All models are released under the Apache 2.0 license.
Ministrals :
https://huggingface.co/collections/mistralai/ministral-3
Mistral Large 3:
https://huggingface.co/collections/mistralai/mistral-large-3
Today, we announce Mistral 3, the next generation of Mistral models. Mistral 3 includes three state-of-the-art small, dense models (14B, 8B, and 3B) and Mistral Large 3 – our most capable model to date – a sparse mixture-of-experts trained with 41B active and 675B total parameters.
All models are released under the Apache 2.0 license.
Ministrals :
https://huggingface.co/collections/mistralai/ministral-3
Mistral Large 3:
https://huggingface.co/collections/mistralai/mistral-large-3
- 2 replies
posted
an
update
about 2 months ago
Post
1768
I'm excited to share that https://installama.sh is up and running! 🚀
On Linux / macOS / FreeBSD it is easier than ever:
And Windows just joined the party 🥳
Stay tuned for new backends on Windows!
On Linux / macOS / FreeBSD it is easier than ever:
curl https://installama.sh | shAnd Windows just joined the party 🥳
irm https://installama.sh | iexStay tuned for new backends on Windows!
posted
an
update
2 months ago
Post
496
🚀
The fastest way to install and run
We are expanding hardware and OS support to make local AI even more accessible. This includes:
🌋 Vulkan support for Linux on
😈 FreeBSD support (CPU backend) on
✨ Lots of small optimizations and improvements under the hood.
Give it a try right now:
installama.sh update: Vulkan & FreeBSD support added!The fastest way to install and run
llama.cpp has just been updated!We are expanding hardware and OS support to make local AI even more accessible. This includes:
🌋 Vulkan support for Linux on
x86_64 and aarch64.😈 FreeBSD support (CPU backend) on
x86_64 and aarch64 too.✨ Lots of small optimizations and improvements under the hood.
Give it a try right now:
curl angt.github.io/installama.sh | MODEL=unsloth/Qwen3-4B-GGUF:Q4_0 sh
posted
an
update
2 months ago
Post
2035
One command line is all you need...
...to launch a local llama.cpp server on any Linux box or any Metal-powered Mac 🚀
Learn more: https://github.com/angt/installama.sh
...to launch a local llama.cpp server on any Linux box or any Metal-powered Mac 🚀
curl angt.github.io/installama.sh | MODEL=unsloth/gpt-oss-20b-GGUF shLearn more: https://github.com/angt/installama.sh
reacted to
AdinaY's
post with 🔥
6 months ago
Post
3564
Qwen3-30B-A3B-Thinking-2507 🔥 latest step in scaling thinking capabilities from Alibaba Qwen team.
Qwen/Qwen3-30B-A3B-Thinking-2507-FP8
✨ 30B total / 3B active - Apache 2.0
✨ Native 256K context
✨ SOTA coding, alignment, agentic reasoning
Qwen/Qwen3-30B-A3B-Thinking-2507-FP8
✨ 30B total / 3B active - Apache 2.0
✨ Native 256K context
✨ SOTA coding, alignment, agentic reasoning
reacted to
IlyasMoutawwakil's
post with 🔥
6 months ago
Post
3512
🚀 Optimum: The Last v1 Release 🚀
Optimum v1.27 marks the final major release in the v1 series. As we close this chapter, we're laying the groundwork for a more modular and community-driven future:
- Optimum v2: A lightweight core package for porting Transformers, Diffusers, or Sentence-Transformers to specialized AI hardware/software/accelerators..
- Optimum‑ONNX: A dedicated package where the ONNX/ONNX Runtime ecosystem lives and evolves, faster-moving and decoupled from the Optimum core.
🎯 Why this matters:
- A clearer governance path for ONNX, fostering stronger community collaboration and improved developer experience..
- Enable innovation at a faster pace in a more modular, open-source environment.
💡 What this means:
- More transparency, broader participation, and faster development driven by the community and key actors in the ONNX ecosystem (PyTorch, Microsoft, Joshua Lochner 👀, ...)
- A cleaner, more maintainable core Optimum, focused on extending HF libraries to special AI hardware/software/accelerators tooling and used by our partners (Intel Corporation, Amazon Web Services (AWS), AMD, NVIDIA, FuriosaAI, ...)
🛠️ Major updates I worked on in this release:
✅ Added support for Transformers v4.53 and SmolLM3 in ONNX/ONNXRuntime.
✅ Solved batched inference/generation for all supported decoder model architectures (LLMs).
✨ Big shoutout to @echarlaix for leading the refactoring work that cleanly separated ONNX exporter logic and enabled the creation of Optimum‑ONNX.
📝 Release Notes: https://lnkd.in/gXtE_qji
📦 Optimum : https://lnkd.in/ecAezNT6
🎁 Optimum-ONNX: https://lnkd.in/gzjyAjSi
#Optimum #ONNX #OpenSource #HuggingFace #Transformers #Diffusers
Optimum v1.27 marks the final major release in the v1 series. As we close this chapter, we're laying the groundwork for a more modular and community-driven future:
- Optimum v2: A lightweight core package for porting Transformers, Diffusers, or Sentence-Transformers to specialized AI hardware/software/accelerators..
- Optimum‑ONNX: A dedicated package where the ONNX/ONNX Runtime ecosystem lives and evolves, faster-moving and decoupled from the Optimum core.
🎯 Why this matters:
- A clearer governance path for ONNX, fostering stronger community collaboration and improved developer experience..
- Enable innovation at a faster pace in a more modular, open-source environment.
💡 What this means:
- More transparency, broader participation, and faster development driven by the community and key actors in the ONNX ecosystem (PyTorch, Microsoft, Joshua Lochner 👀, ...)
- A cleaner, more maintainable core Optimum, focused on extending HF libraries to special AI hardware/software/accelerators tooling and used by our partners (Intel Corporation, Amazon Web Services (AWS), AMD, NVIDIA, FuriosaAI, ...)
🛠️ Major updates I worked on in this release:
✅ Added support for Transformers v4.53 and SmolLM3 in ONNX/ONNXRuntime.
✅ Solved batched inference/generation for all supported decoder model architectures (LLMs).
✨ Big shoutout to @echarlaix for leading the refactoring work that cleanly separated ONNX exporter logic and enabled the creation of Optimum‑ONNX.
📝 Release Notes: https://lnkd.in/gXtE_qji
📦 Optimum : https://lnkd.in/ecAezNT6
🎁 Optimum-ONNX: https://lnkd.in/gzjyAjSi
#Optimum #ONNX #OpenSource #HuggingFace #Transformers #Diffusers
posted
an
update
6 months ago
Post
281
The new
I couldn't resist writing a blog post about it:
https://huggingface.co/blog/angt/your-own-gpu-powered-image-generator-with-hf-jobs
hf jobs CLI is absolutely awesome!I couldn't resist writing a blog post about it:
https://huggingface.co/blog/angt/your-own-gpu-powered-image-generator-with-hf-jobs
posted
an
update
7 months ago
Post
319
Just published: Nano-vLLM meets Inference Endpoints
I show how to bind Nano-vLLM (supporting Qwen3-0.6B) to a web service — and deploy it easily on Hugging Face Inference Endpoints.
Minimalist engine, maximum fun!
https://huggingface.co/blog/angt/nano-vllm-meets-inference-endpoints
I show how to bind Nano-vLLM (supporting Qwen3-0.6B) to a web service — and deploy it easily on Hugging Face Inference Endpoints.
Minimalist engine, maximum fun!
https://huggingface.co/blog/angt/nano-vllm-meets-inference-endpoints
