全站搜索

AI 模型 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 Flash 是 inclusionAI 推出的一款混合推理专家模型，其活跃参数数量为 250 亿，总参数量为 5600 亿。

• 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