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miamorales

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\ generate prompt as danbooru style tags \ a one line caption for the image \ a structured caption format which detects the position of the subjects in the image \ a very detailed description for the image \ image composition analysis mode \ a mixed caption style of more detailed caption and tags, this is extremely useful for FLUX model when using T5XXL and CLIP_L together. A new node in MiaoshouTagger ComfyUI is added to support this instruction. \ Combine the power of mixed caption with analyze. For version 2.0, you will notice the following 1. \ along with a beta node in ComfyUI for partial image analysis 2. A new instruction for \ 3. A much improve accuracy for \ , \ and \ A detailed use and install instruction is already there. (If you have already installed MiaoshouAI Tagger, you need to update the node in ComfyUI Manager first or use git pull to get the latest update.)

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\ generate prompt as danbooru style tags \ a one line caption for the image \ a structured caption format which detects the position of the subjects in the image \ a very detailed description for the image \ image composition analysis mode \ a mixed caption style of more detailed caption and tags, this is extremely useful for FLUX model when using T5XXL and CLIP_L together. A new node in MiaoshouTagger ComfyUI is added to support this instruction. \ Combine the power of mixed caption with analyze. For version 2.0, you will notice the following 1. \ along with a beta node in ComfyUI for partial image analysis 2. A new instruction for \ 3. A much improve accuracy for \ , \ and \ A detailed use and install instruction is already there. (If you have already installed MiaoshouAI Tagger, you need to update the node in ComfyUI Manager first or use git pull to get the latest update.)

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vare1

miatensor

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Uncensored Qwen3.8-27B, published as GGUF quantizations with the multi-token prediction (MTP) head retained and verified. Refusal behaviour has been **substantially reduced**, not eliminated — see Measured behaviour for the numbers. Capabilities, training data, and architecture are otherwise unchanged. > **MTP tensors verified, not assumed.** Abliteration drops the `mtp.*` tensors: the model > is re-saved through transformers, which does not carry the MTP head, while `config.json` > still advertises it. They are grafted back from the base checkpoint and every file is > inspected after quantization — see Method and Verification.

Text generation
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More details about the infinity inference project please refer to the Github: Infinity. To deploy files with the infinity_emb pip package. Recommended is `device="cuda", engine="torch"` with flash attention on gpu, and `device="cpu", engine="optimum"` for onnx inference. If you have any question or suggestion related to this project, feel free to open an issue or pull request. You also can email Michael Feil (infinity at michaelfeil.eu).

Embeddings & similarity
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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).

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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed]

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