ABabrichr·Dec 17, 2023
Very promising, excited to learn more!
Any thoughts on State Space Models?
Eg:
https://github.com/havenhq/mamba-chat
https://arxiv.org/abs/2311.18257
In Transformers on Chipsmidrender
mamba-chat
Python2023–2023
midrender / mamba-chat
mamba-chat
Mamba-Chat: A chat LLM based on the state-space model architecture 🐍
2Distinct people
2Mentions
0Explicit recommenders
942GitHub stars
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Mamba-Chat: A chat LLM based on the state-space model architecture 🐍
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This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM UTC.
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HN mentions by day2 dated mentions
Observed mentions: 2023-12-07 04:10:07 UTC to 2023-12-17 06:22:39 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Dec 7 | 2023-12-07 00:00:00 UTC | 2023-12-08 00:00:00 UTC | 1 | 1 | 0 |
| Dec 8 | 2023-12-08 00:00:00 UTC | 2023-12-09 00:00:00 UTC | 0 | 0 | 0 |
| Dec 9 | 2023-12-09 00:00:00 UTC | 2023-12-10 00:00:00 UTC | 0 | 0 | 0 |
| Dec 10 | 2023-12-10 00:00:00 UTC | 2023-12-11 00:00:00 UTC | 0 | 0 | 0 |
| Dec 11 | 2023-12-11 00:00:00 UTC | 2023-12-12 00:00:00 UTC | 0 | 0 | 0 |
| Dec 12 | 2023-12-12 00:00:00 UTC | 2023-12-13 00:00:00 UTC | 0 | 0 | 0 |
| Dec 13 | 2023-12-13 00:00:00 UTC | 2023-12-14 00:00:00 UTC | 0 | 0 | 0 |
| Dec 14 | 2023-12-14 00:00:00 UTC | 2023-12-15 00:00:00 UTC | 0 | 0 | 0 |
| Dec 15 | 2023-12-15 00:00:00 UTC | 2023-12-16 00:00:00 UTC | 0 | 0 | 0 |
| Dec 16 | 2023-12-16 00:00:00 UTC | 2023-12-17 00:00:00 UTC | 0 | 0 | 0 |
| Dec 17 | 2023-12-17 00:00:00 UTC | 2023-12-18 00:00:00 UTC | 1 | 0 | 1 |
What Hacker News says
2 sourcesShow HN: Mamba-Chat – A Chat LLM Based on State Space Models
Hey everyone! Many of you might have come across the Mamba paper a few days ago, which introduced an LLM based on a state space model architecture. The Mamba architecture is quite useful as its complexity scales subquadratically with input length and is therefore way more efficient than transformer models: https://github.com/state-spaces/mamba
I got really excited about the paper, so I decided to fine-tune the model on a chat dataset. It turns that this actually worked quite well! The model is quite suitable for casual chatting, which honestly surprised me given that it only has 2.8B parameters and the base model was only trained on the Pile. It's quite exciting that we might have a serious candidate for an architecture that could dethrone transformers.
You can find both my fine-tuning and inference code here: https://github.com/havenhq/m