kingdy retweetledi
kingdy
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kingdy retweetledi
Introducing the Official Polymarket Rust CLOB Client 🦀
One of the first things I ended up working on after joining Polymarket was a Rust client for the CLOB.
There were already good clients in other languages, but a lot of builders were asking for native Rust. I also wanted to introduce Rust into the Polymarket organization and ecosystem, especially for people running trading systems where performance and type safety are critical.
With that, I decided to design and implement rs-clob-client, inspired by the existing Python and Typescript clients, and recently open-sourced it. It's focused on ergonomics and performance.
If you're building on the CLOB and prefer Rust, hopefully this saves you some time. @PolymarketBuild
Enjoy!
github.com/Polymarket/rs-…
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The first 24/7 neo-brokerage.
Trade perpetual markets for crypto, equities, and private assets. Move USD in and out, all from one unified account.
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@QuoteChain_AI How do you get a million dollars in crypto investing?
Start with ten million.
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Block 36
Boosted topic: None
Replies recognized by AI in the block: 10
Block reward: 33333 QT
Top recognition:
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Quick tutorial on how to run Llama 4 within 10 minutes
1. rent 4x H100 instance on app.hyperbolic.xyz/compute
(Llama 4 Scout has 109B parameters in bf16, so the weights are already 218GB)
2. open a terminal tool and SSH into the machine
3. run the following commands:
>> sudo apt-get update && sudo apt-get install -y python3-pip
>> pip install -U vllm
>> pip install -U "huggingface_hub[cli]"
4. get an access token on @huggingface website and run
>> huggingface-cli login
5. use @vllm_project to serve Llama 4
>> vllm serve meta-llama/Llama-4-Scout-17B-16E-Instruct --tensor-parallel-size 4 --max-model-len 10000
6. open a new terminal and call the API to know "What can I do in SF?":
>> curl http://localhost:8000/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "meta-llama/Llama-4-Scout-17B-16E-Instruct",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "What can I do in SF?"}
]
}'
It's just that simple ;) A big thank you to @AIatMeta and @vllm_project for making it easy to access the best open intelligence!
AI at Meta@AIatMeta
Today is the start of a new era of natively multimodal AI innovation. Today, we’re introducing the first Llama 4 models: Llama 4 Scout and Llama 4 Maverick — our most advanced models yet and the best in their class for multimodality. Llama 4 Scout • 17B-active-parameter model with 16 experts. • Industry-leading context window of 10M tokens. • Outperforms Gemma 3, Gemini 2.0 Flash-Lite and Mistral 3.1 across a broad range of widely accepted benchmarks. Llama 4 Maverick • 17B-active-parameter model with 128 experts. • Best-in-class image grounding with the ability to align user prompts with relevant visual concepts and anchor model responses to regions in the image. • Outperforms GPT-4o and Gemini 2.0 Flash across a broad range of widely accepted benchmarks. • Achieves comparable results to DeepSeek v3 on reasoning and coding — at half the active parameters. • Unparalleled performance-to-cost ratio with a chat version scoring ELO of 1417 on LMArena. These models are our best yet thanks to distillation from Llama 4 Behemoth, our most powerful model yet. Llama 4 Behemoth is still in training and is currently seeing results that outperform GPT-4.5, Claude Sonnet 3.7, and Gemini 2.0 Pro on STEM-focused benchmarks. We’re excited to share more details about it even while it’s still in flight. Read more about the first Llama 4 models, including training and benchmarks ➡️ go.fb.me/gmjohs Download Llama 4 ➡️ go.fb.me/bwwhe9
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