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AI 模型 84757

• gemma-2b-sfp-cpp↗

  Google

• paligemma-3b-ft-rsvqa-hr-224↗

  Google

• oss-jev-qwen05-decision-noul-bal↗

  gyanbhambhani

• moonshine-streaming-tiny-gguf↗

  handy-computer

• opus-mt-en-zh↗

  Helsinki-NLP

  * source group: English * target group: Chinese * OPUS readme: eng-zho * model: transformer * source language(s): eng * target language(s): cjy_Hans cjy_Hant cmn cmn_Hans cmn_Hant gan lzh lzh_Hans nan wuu yue yue_Hans yue_Hant * model: transformer * pre-processing: normalization + SentencePiece (spm32k,spm32k) * a sentence initial language token is required in the form of `>>id<<` (id = valid target language ID) * download original weights: opus-2020-07-17.zip * test set translations: opus-2020-07-17.test.txt * test set scores: opus-2020-07-17.eval.txt - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-zho/README.md

• HiDream-I1-Full↗

  HiDream-ai

• stack-edu-classifier-go↗

  HuggingFaceTB

• ci-random-llama3-8b↗

  hyper-accel

  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).

• tiny-random-llama↗

  hyper-accel

• granite-4.0-h-tiny-GGUF↗

  ibm-granite

  > [!NOTE] > This repository contains models that have been converted to the GGUF format with various quantizations from an IBM Granite base model. > > Please reference the base model's full model card here: > https://huggingface.co/ibm-granite/granite-4.0-h-tiny