QUAN-Transcribe-1.0
top 81% by trending score
QUAN-Transcribe-1.0 is a automatic-speech-recognition model in the Audio category, published by qnguyen3. These figures are Hugging Face's own signals — downloads, likes and trending score — captured by Model Radar and refreshed daily. For weights, model card and usage, open it on Hugging Face.
Surge analysis
why it's on the radarHugging Face publishes a single trending score; it doesn't expose the formula. So Model Radar reads the surge from the four public signals that move with it — momentum, adoption, community and recency — each normalized against the tracked field, then weighted into a 0–100 composite. The weights are ours, and shown below. No hidden inputs.
Radar position over time
movementWhere QUAN-Transcribe-1.0 sits on the radar, tracked daily — new to the radar since the prior run. position movement fills in as the radar refreshes daily.
In context
vs. category peersHow this model stacks up against the other 15 Audio models on the radar. The filled bar is this model; the tick is the category-peer median. Downloads and likes use a log scale (they span orders of magnitude).
Bars are normalized against the most extreme model in the whole radar, so a near-full bar means category-leading. Peer median = the middle model of the 15 in this category.
Recency
last updateWhere this model's last update lands on a freshness scale — fresh (<14d), recent (14–60d), or older.
Category peers
Audio · 15 modelsOther Audio models ranked near this one — click through to compare.
📛 Embed this badge
rank badgeShow your live Model Radar rank in your README — it updates daily and links back here.
Primary links
on hugging faceGo straight to the source — everything here links back to Hugging Face.