Running on Zero
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stuntd
🧭
Zero-shot Laya vs heads stuntd trained per decision
Denis PRO
pollix
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Recent Activity
repliedto their post about 1 hour ago
First stuntd model is on the Hub :)
pollix/stuntd-support-triage is three small heads on the Laya encoder that triage a support ticket in one request: category, urgency and needs_human. About 50 MB each, all three answers come back at a p50 of 71ms through the daemon.
On 1,000 tickets they never saw, each head answers on its own when it's sure: category 99.9%, needs_human 92%, urgency 76%. A ticket only skips the big model when all three are sure, that's 72.7% of them, and all three are right on 97.1% of those.
It's the support demo from the repo, so the tickets are generated and the teacher is a rule. The point is to show what a head looks like and how fast it is, then you train the same thing on your own traffic with your own LLM as the teacher.
```
hf download pollix/stuntd-support-triage --local-dir support-heads
```
Model: https://huggingface.co/pollix/stuntd-support-triage
Everything in one place: https://huggingface.co/collections/pollix/stuntd-6abe0a33303828e10c72ab41
Code: https://github.com/bladedevoff/stuntd reacted to theirpost with 🔥 about 3 hours ago
First stuntd model is on the Hub :)
pollix/stuntd-support-triage is three small heads on the Laya encoder that triage a support ticket in one request: category, urgency and needs_human. About 50 MB each, all three answers come back at a p50 of 71ms through the daemon.
On 1,000 tickets they never saw, each head answers on its own when it's sure: category 99.9%, needs_human 92%, urgency 76%. A ticket only skips the big model when all three are sure, that's 72.7% of them, and all three are right on 97.1% of those.
It's the support demo from the repo, so the tickets are generated and the teacher is a rule. The point is to show what a head looks like and how fast it is, then you train the same thing on your own traffic with your own LLM as the teacher.
```
hf download pollix/stuntd-support-triage --local-dir support-heads
```
Model: https://huggingface.co/pollix/stuntd-support-triage
Everything in one place: https://huggingface.co/collections/pollix/stuntd-6abe0a33303828e10c72ab41
Code: https://github.com/bladedevoff/stuntd posted an update about 3 hours ago
First stuntd model is on the Hub :)
pollix/stuntd-support-triage is three small heads on the Laya encoder that triage a support ticket in one request: category, urgency and needs_human. About 50 MB each, all three answers come back at a p50 of 71ms through the daemon.
On 1,000 tickets they never saw, each head answers on its own when it's sure: category 99.9%, needs_human 92%, urgency 76%. A ticket only skips the big model when all three are sure, that's 72.7% of them, and all three are right on 97.1% of those.
It's the support demo from the repo, so the tickets are generated and the teacher is a rule. The point is to show what a head looks like and how fast it is, then you train the same thing on your own traffic with your own LLM as the teacher.
```
hf download pollix/stuntd-support-triage --local-dir support-heads
```
Model: https://huggingface.co/pollix/stuntd-support-triage
Everything in one place: https://huggingface.co/collections/pollix/stuntd-6abe0a33303828e10c72ab41
Code: https://github.com/bladedevoff/stuntdOrganizations
