Torchcast Decision 4B
torchcast-ai · Kit
A 4B decision model built on Qwen3.5-4B that returns yes/no probabilities, choice distributions and score distributions in one pass without generating text. Fo…
torchcast-ai · Kit
A 4B decision model built on Qwen3.5-4B that returns yes/no probabilities, choice distributions and score distributions in one pass without generating text. Fo…
stephenlb · Kit
Answers yes/no, multiple-choice and score questions about a text with a probability for each answer, using a Gemma 4 12B base with a small decision head. For d…
microsoft · Kit
Turns text in many languages into embedding vectors for search, clustering, similarity, classification and reranking. Made for developers who run semantic sear…
ibm-granite · Kit
Handles summaries, classification, extraction, question answering, RAG, code tasks and tool calling in 12 languages with a 340M-parameter instruct model from I…
google-t5 · Kit
A 220 million parameter text-to-text model that handles translation between English, French, Romanian and German, and also summarization, question answering an…
google-bert · Kit
Fills in masked words and extracts text features in 104 languages. A case-sensitive BERT base model meant to be fine-tuned for classification, tagging and ques…
doofz · Kit
Answers typed questions about a ticket, email or document in one fast pass, with calibrated probabilities, extracted numbers, excerpts and citations. A 322M mu…
answerdotai · Kit
Predicts a hidden word in English text or code, and after fine-tuning serves as a larger long-context encoder for search, classification and retrieval. Made fo…
answerdotai · Kit
Predicts a hidden word in English text or code, and after fine-tuning serves as a long-context encoder for search, classification and retrieval. Made for devel…
SupersonicLabs · Kit
Takes a text, a question and a list of possible answers, and picks the best one for classification, routing, ordered scores and yes-or-no calls. A 144M model f…
Poindexter-Labs · Kit
Returns structured decisions from plain-language context: pick one option, judge a yes or no claim, or score an item against a rubric. For developers building…
facebook · Kit
Turns videos and images into embeddings for video classification, retrieval, or as the video encoder of a vision-language model. Built by FAIR at Meta for deve…
distilbert · Kit
A small, fast English language model distilled from BERT base, with 67M parameters. Fills in masked words and is mainly meant to be fine-tuned for classificati…
BAAI · Kit
Turns Chinese text into dense vectors for search, classification, clustering and semantic matching. A 24M-parameter BGE embedding model from BAAI under the MIT…
dmis-lab · Kit
Predicts masked words in English text and gives you a pre-trained encoder with a 32K context to fine-tune for classification or retrieval. A fill-mask model fr…
google-bert · Kit
Fills in masked words and extracts text features for English. The uncased BERT base model from Google, meant to be fine-tuned for classification, tagging and q…
nomic-ai · Kit
Turns English text into embedding vectors for search, clustering and classification, and the vectors can be cut to a smaller size. It suits developers building…
Sense-X · Kit
A Gradio demo that runs the Sense-X UniFormer video model on a clip and reports its class, with three example videos included. Suits students and developers wh…
Sense-X · Kit
A Gradio demo that runs the Sense-X UniFormer image model on a picture and reports its class, with a few example photos included. Suits students and developers…
keras-io · Kit
Shows a forest-based classifier built in TensorFlow inside a Gradio page, from an example by Khalid Salama and adapted by Tannia Dubon. For students and develo…