全站搜索

AI 模型 85003

• VideoChat-Flash-Qwen2-7B_res448↗

  OpenGVLab

  VideoChat-Flash-7B is constructed upon UMT-L (300M) and Qwen2-7B, employing only **16 tokens per frame**. By leveraging Yarn to extend the context window to 128k (Qwen2's native context window is 32k), our model supports input sequences of up to approximately **10,000 frames**. > Note: Due to a predominantly English training corpus, the model only exhibits basic Chinese comprehension, to ensure optimal performance, using English for interaction is recommended. First, you need to install flash attention2 and some other modules. We provide a simple installation example below:

• OpenScholar_Retriever↗

  OpenSciLM

• EuroDense-435M↗

  OPI-PIB

• tiny-random-llama↗

  optimum-internal-testing

• tiny-random-qwen3↗

  optimum-internal-testing

  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

• Ternary-Bonsai-2-27B-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS-MLX-Mixed-2-8bit↗

  PhillyLabs

• Mistral-Gutenberg-Doppel-7B-FFT-GGUF↗

  QuantFactory

• Qwen-1_8B-Chat-Int4↗

  阿里巴巴 · Qwen

• Qwen3 Omni 30B A3B (Reasoning)↗

  阿里巴巴 · Qwen

• roberta-base-on-cuad↗

  Rakib

  Read: An Open Source Contractual Language Understanding Application Using Machine Learning for detailed information on training procedure, dataset preprocessing and evaluation.