josefprusa/ThinkingCap-Qwen3.6-27B-int4-AutoRound-v1 Text Generation β’ 6B β’ Updated about 1 month ago β’ 12.1k β’ 50
view post Post 118 Structured financial facts, each linked to the character in the filing it came from π°πToday I am introducing two datasets and a model trained on them: StockAlloy/filedfact-passages A passage-complete dataset of phrases and the embedded financial facts. StockAlloy/filedfact-100kA fact-sampled version- one grounded financial fact per row, deep-linked to its source. StockAlloy/filedfact-qwen3-8bAn 8B model fine-tuned to read a filing passage and return the facts as JSON. Kroam1/filedfact-demoLive demo - paste a passage, see the facts. See translation 1 reply Β· π 3 3 + Reply
Running on Zero Agents 1 FiledFact β SEC Fact Extraction π 1 Paste an SEC filing passage β XBRL-aligned facts as JSON
view post Post 20109 Qwen 3.6 27B Fine tune exceed 700 ARC-C for both 8 and 4 bit.A new level of uncensored performance the puts this model squarely at "closed source" level of intelligence.Model exceeds all critical benchmarks for both Qwen 3.6 27B AND Qwen 3.6 35B-A3B... and not by a little either.Neo Imatrix MAX ggufs in both regular and MTP quants.Benchmarks for Qwen 3.6 27B org and tuned, as well as Qwen 3.6 35B-A3B are up at the repo. DavidAU/Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-NEO-MAX-MTP-GGUF See translation 20 replies Β· β€οΈ 17 17 π 8 8 + Reply
Running on Zero Agents 1 FiledFact β SEC Fact Extraction π 1 Paste an SEC filing passage β XBRL-aligned facts as JSON