Hugging Face
Models
Datasets
Spaces
Buckets
new
Docs
Enterprise
Pricing
Website
Tasks
HuggingChat
Collections
Languages
Organizations
Community
Blog
Posts
Daily Papers
Hardware
Learn
Discord
Forum
GitHub
Solutions
Team & Enterprise
Hugging Face PRO
Enterprise Support
Inference Providers
Inference Endpoints
Storage Buckets
Log In
Sign Up
๐๏ธ
Building on HF
11.6
TFLOPS
Denis
PRO
pollix
6
1
3
Follow
ginigen-ai's profile picture
nedzen's profile picture
Anurag-ucb's profile picture
12 followers
ยท
2 following
AI & ML interests
None yet
Recent Activity
reacted
to
their
post
with ๐
about 18 hours ago
stuntd 0.1.3 is out, and most of it started with a comment under my last post :) @dipankarsarkar ran the support demo himself and showed my "1,000 tickets the heads never saw" were new wording of known tickets, not new kinds. On templates left out of training the heads were sure on 40% of tickets and right on only 61% of those. They also answered "what's the weather in Paris" like it was a billing ticket. So now every head keeps the encoder vectors of what it trained on, and anything far from all of them goes to the big model no matter how confident the head is. Screenshot is the same three requests with the gate off and on. It's local Jev mode with no provider, so the gate hands them to zero-shot Laya. Behind OpenAI or Anthropic they'd go to your model. On the support demo it costs about 6 points of local answers on normal tickets (76.6% to 70.6%, still 97% right), and tickets from unseen templates go from 40% answered locally to 0. Funny detail: a ticket I typed by hand counted as new too, these demo heads only ever saw 20 templates. Also in this one: auto retrain counts distinct texts and waits between runs, report shows intervals, import skips duplicates, site rm/rename, /healthz and stuntd stop. ``` pip install -U stuntd ``` https://github.com/bladedevoff/stuntd/releases/tag/v0.1.3
updated
a model
about 18 hours ago
pollix/stuntd-support-triage
posted
an
update
about 18 hours ago
stuntd 0.1.3 is out, and most of it started with a comment under my last post :) @dipankarsarkar ran the support demo himself and showed my "1,000 tickets the heads never saw" were new wording of known tickets, not new kinds. On templates left out of training the heads were sure on 40% of tickets and right on only 61% of those. They also answered "what's the weather in Paris" like it was a billing ticket. So now every head keeps the encoder vectors of what it trained on, and anything far from all of them goes to the big model no matter how confident the head is. Screenshot is the same three requests with the gate off and on. It's local Jev mode with no provider, so the gate hands them to zero-shot Laya. Behind OpenAI or Anthropic they'd go to your model. On the support demo it costs about 6 points of local answers on normal tickets (76.6% to 70.6%, still 97% right), and tickets from unseen templates go from 40% answered locally to 0. Funny detail: a ticket I typed by hand counted as new too, these demo heads only ever saw 20 templates. Also in this one: auto retrain counts distinct texts and waits between runs, report shows intervals, import skips duplicates, site rm/rename, /healthz and stuntd stop. ``` pip install -U stuntd ``` https://github.com/bladedevoff/stuntd/releases/tag/v0.1.3
View all activity
Organizations
pollix
's models
1
Sort:ย Recently updated
pollix/stuntd-support-triage
Text Classification
โข
Updated
about 18 hours ago
โข
3