Qwen3.8-2B-Function-Calling-xLAM-Unsloth-GGUF
ermiaazarkhalili基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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Qwen3.8-4B-Function-Calling-xLAM-Unsloth-GGUF
ermiaazarkhalili基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Qwen3.8-9B-Function-Calling-xLAM-Unsloth-GGUF
ermiaazarkhalili基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Qwen3.8-9B-SFT-Fable5-Glint-GGUF
ermiaazarkhalili基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗VibeThinker-3B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF
ermiaazarkhalili基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗stewmind-1.7b
Erog0291基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗stewmind-1.7b-ultra
Erog0291基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗This model is xlm-roberta-base fine-tuned to classify descriptions of activities into NACE Rev. 2 codes. The data used to fine-tune the model consist of 2.5 million descriptions of activities from Norwegian and Danish businesses. To improve the model's multilingual performance, random samples of the Norwegian and Danish descriptions were machine translated into the following languages: - English - German - Spanish - French - Finnish - Polish
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View details ↗Qwen3-4b-tcomanr-merge-v2.7
ertghiu256基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Qwen3.5-0.8b-instruct-v2-gguf
ertghiu256基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗assert-ai
erukude基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗cornvit
erukude基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗galaxy-simplifier
erukude基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗multiagent-orchestrator
erukude基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗omni-json
erukude基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗gpt2-mini
erwanfA smaller GPT-2 model with (only) 39M parameters. It was pretrained on a subset of OpenWebText, the open-source version of the pretraining dataset used by OpenAI for the original GPT-2 models. The purpose of this model is mainly for research and education. Its small size allows for fast experiments in resource-limited settings, while still being able of generating complex and coherent text. The architecture relies on the GPT-2 model, with smaller dimensions and less layers. It uses the same tokenizer as GPT-2. We used the first 2M rows from the OpenWebText dataset, out of which we use 1k for test and validation sets.
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View details ↗polka-1.1b
eryk-mazus基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗polka-1.1b-chat
eryk-mazus基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Nev-2B-GGUF
EryriLabs基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Ornith-1.5-35B-A3B-BigBang-MTP-GGUF
EryriLabs基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗pocket-tts-GGUF
EryriLabs基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗litter-detection-yolov8
esapzoi- **Base Model**: yolov8n.pt - **Task**: Object Detection - **Classes**: Litter - **Framework**: PyTorch + Ultralytics YOLO Use this model for litter detection systems, environmental monitoring, and waste management applications.
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View details ↗Gemma-4-31B-IT-NVFP4-GGUF
esatapedico基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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