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AI モデル 84760

• Idefics3-8B-Llama3↗

  HuggingFaceM4

  Idefics3 is an open multimodal model that accepts arbitrary sequences of image and text inputs and produces text outputs. The model can answer questions about images, describe visual content, create stories grounded on multiple images, or simply behave as a pure language model without visual inputs. It improves upon Idefics1 and Idefics2, significantly enhancing capabilities around OCR, document understanding and visual reasoning. - **Developed by:** Hugging Face - **Model type:** Multi-modal model (image+text) - **Language(s) (NLP):** en - **License:** Apache 2.0 - **Parent Models:** google/siglip-so400m-patch14-384 and meta-llama/Meta-Llama-3.1-8B-Instruct - **Resources for more information:** - Idefics1 paper: OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents - Idefics2 paper: What matters when building vision-language models? - Idefics3 paper: Building and better understanding vision-language models: insights and future directions `Idefics3-8B` can be used to perform inference on multimodal (image + text) tasks in which the input is composed of a text query along with one (or multiple) image(s). Text and images can be arbitrarily interleaved. That includes image captioning, visual question answering, etc. These model does not support image generation.

• granite-3.0-8b-base↗

  ibm-granite

  **Model Summary:** Granite-3.0-8B-Base is a decoder-only language model to support a variety of text-to-text generation tasks. It is trained from scratch following a two-stage training strategy. In the first stage, it is trained on 10 trillion tokens sourced from diverse domains. During the second stage, it is further trained on 2 trillion tokens using a carefully curated mix of high-quality data, aiming to enhance its performance on specific tasks. **Supported Languages:** English, German, Spanish, French, Japanese, Portuguese, Arabic, Czech, Italian, Korean, Dutch, and Chinese. Users may finetune Granite 3.0 models for languages beyond these 12 languages. **Intended use:** Prominent use cases of LLMs in text-to-text generation include summarization, text classification, extraction, question-answering, and more. All Granite Base models are able to handle these tasks as they were trained on a large amount of data from various domains. Moreover, they can serve as baseline to create specialized models for specific application scenarios.

• redcraft-minimax-h3-a2a-redmix↗

  jasperz111

• nova-furry-xl-il-v120-sdxl↗

  John6666

  Original model is here. This model created by Crody.

• Qwen3.8-35B-A3B-Distill-oQ5e-vision↗

  Johneeee

• ConvTasNet_Libri2Mix_sepclean_16k↗

  JorisCos

• Gemma2-2b-Spanish-Roleplay-GGUF↗

  Kukedlc

• rwkv-6-finch-7b-gguf↗

  latestissue

• c67-h20↗

  lfgidjg34dd

• Experiment27Experiment29-7B-GGUF↗

  MaziyarPanahi