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AI 모델 85004

• Hy-MT2-1.8B-JP-Manga-Finetune-v5-GGUF↗

  fumetodev

• Flux-Double-Exposure-LoRA↗

  gokaygokay

• t5-efficient-tiny-nl16↗

  Google

• tapas-base-finetuned-tabfact↗

  Google

• Qwen3-ASR-1.7B-RKLLM↗

  happyme531

• HunyuanVideo↗

  腾讯

• Jais-3-MoVA-36B-A4B-MLX-bf16↗

  IFM

• Ling 3.1 Flash↗

  inclusionai

  Ling 3.1 Flash는 inclusionAI의 하이브리드 추론 혼합-전문가 모델로, 총 560B 파라미터 중 25B 개의 활성 파라미터를 갖추고 있습니다.

• nach0_base↗

  insilicomedicine

  Tasks Datasets used for training and evaluation. Colour represents the type of tasks. Yellow and blue datasets are single-domain, typically requiring regression/classification losses or generation in the target domain (natural language or SMILES strings). Gradients from yellow to blue represent cross-domain generation tasks that require natural language input and SMILES output, or vise versa. The simplest way to use the large version of the model is to run the megatron_t5_seq2seq_eval.py or megatron_t5_seq2seq_finetune.py script. Prior to executing the script, prepare the input (prompts) and output (responses) files and set up the config file. The input file should have prompts on each line, which need to be preprocessed using the `add_special_symbols` function mentioned above.

• japanese-sentiment-analysis↗

  jarvisx17