Nicheloom

Market intelligence for builders — see what's gaining traction before it's crowded.

typed-lm

Single-forward-pass semantic routing in Rust: turn dense LLMs (Llama, Qwen, Mistral, Gemma) into a typed decision API with LoRA/QLoRA training and FP8/FP4 quantization, built on Candle.

Details

External ID
1387773949
Source
GITHUB
Company
—
Product
typed-lm
Website domain
github.io
Launched
Sept. 25, 2026
Cohort
—
Upvotes
9
Upvotes percentile
0.21822956699974377
Tags
actix-web, candle, classification, huggingface, inference, llm, lora, machine-learning, mlops, nlp, qlora, quantization, rust, semantic-routing, transformer
Fetched at
Sept. 29, 2026, 1:02 a.m.
Updated at
Sept. 29, 2026, 1:02 a.m.

Enrichment

Theme
decision model runtimes and tools
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
semantic routing and typed decision api for llms
Manually corrected
False

Could you build this?

No Implementing single-forward-pass semantic routing, Candle tensor operations, custom LoRA/QLoRA training, and FP8/FP4 quantization in Rust requires deep compiler and ML systems engineering expertise.

What it would actually take: Building typed-lm demands custom Rust implementations on Hugging Face Candle or custom CUDA kernels, hacking the transformer attention heads to project logits at specific positions into categorical decisions. It requires advanced knowledge of GPU memory architectures, low-bit quantization schemes (FP8/FP4), transformer internals, and low-latency systems programming.

Competitors

Other products that read as similar to this one — 1085 launches clear the similarity bar, closest 8 shown.

Attention rank: #786 of 1086 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 330 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a model & infra tool for Fintech yet.