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Ask questions about a YouTube video and get answers drawn from its captions, using a chat model you pick. Videos without captions are transcribed from their audio first.

SkyReels V1 is the first and most advanced open-source human-centric video model.

Reads Turkish license plates in a photo and returns them as text, along with a copy of the image where each car is numbered and each plate is boxed.

Turns a few lines of hiring notes into a formatted job posting in English or Turkish, in one of five tones. CVs or an older posting can be attached as extra context.

MEMO animates a single portrait so it talks or sings along to an audio clip, keeping the face consistent over long videos and matching the expression to the emotion in the voice.

Scores each uploaded CV against a job description you paste in. Each score comes with a written review of qualifications, experience, skills and job fit, and the detailed mode adds the parsed profile.

Reads a batch of CVs and returns one structured record per candidate (contact details, skills, certifications, job history and education) in a combined JSON or CSV file, plus one file per CV.

An 8B clinical chat model from M42, fine-tuned from Llama 3 8B Instruct to answer the medical questions that general-purpose assistants are often tuned to avoid.

A 1.7B-parameter English chat model from Hugging Face's SmolLM2 family, built small enough to run on-device and tuned with SFT and DPO for instruction following and function calling.

Generate synchronized audio for videos using AI. Enhance video content with matching sound effects or create custom audio from text descriptions.

Answers questions from files you upload, such as PDF, Word, PowerPoint or CSV. The chat model you choose writes each answer from the passages that best match the question.

Generate images from a text prompt with a FLUX.1 base model and a LoRA of your choice: a public style listed on Wiro, one of your private LoRAs, or a .safetensors file by URL.

Writes a detailed English description of a video clip, guided by your prompt. Built on THUDM's CogVLM2-Llama3-Caption, the model that captioned training data for CogVideoX.

Writes one detailed English paragraph describing a video clip from start to finish. THUDM built it to caption training data for its CogVideoX text-to-video model.

Suno's Bark reads text aloud in 13 languages with one of 130 voice presets. Cues such as [laughs], [sighs] or lyrics wrapped in ♪ add nonverbal sounds and sung lines.

Cuts the main subject out of a photo and returns it on a transparent background at the original size. BiRefNet is a high-resolution segmentation model that uses gradient maps to keep fine edges.

Turns a text prompt into an image in 1 to 4 sampling steps. Black Forest Labs released it under Apache 2.0, so the model and its images can be used commercially.

Removes the background from photos and returns each subject as a PNG cutout with transparency. One run takes up to 30 images.

Sets a still image in motion, following a text prompt for what should move. The model is I2VGen-XL from Alibaba's Tongyi Lab, with adjustable frame rate and output size.

hair-fast-gan applies the hairstyle and hair color to the input image.