FEnet / README.md
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---
license: mit
language:
- zh
metrics:
- accuracy
base_model:
- microsoft/resnet-50
base_model_relation: quantized
library_name: transformers
pipeline_tag: text-generation
widget:
- src: >-
https://huggingface.co/iSolver-AI/FEnet/resolve/main/xiaohongshu-girls-enndme-1.jpg
example_title: enndme-pic-1
output:
text: Hello my name is Julien
- src: >-
https://huggingface.co/iSolver-AI/FEnet/resolve/main/xiaohongshu-girls-enndme-2.jpg
example_title: enndme-pic-2
output:
- label: POSITIVE
score: 0.8
- src: >-
https://huggingface.co/iSolver-AI/FEnet/resolve/main/xiaohongshu-girls-enndme-3.jpg
example_title: enndme-pic-3
output:
- label: POSITIVE
score: 0.8
tags:
- mlx
- llama
- llama3
- transformers
- Reward Model
---
test webhook
# Paper:
- 来源于HF+arxiv,完整输入HF链接的论文:[F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching](https://huggingface.co/papers/2410.06885)
- 来源于HF+arxiv,完整输入arxiv链接的论文:https://arxiv.org/abs/2410.11817
- 来源于HF+arxiv,仅输入标题+编号的论文:[Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction](2409.18124)
- 来源于HF+arxiv,仅输入标题的论文:Exploring Model Kinship for Merging Large Language Models
- 来源于HF+arxiv,仅输入编号的论文:2410.12381
- 来源于HF+arxiv,输入链接不带https://前缀:arxiv.org/abs/2410.09401
- 仅来源于arxiv,完整输入arxiv链接的论文:[Improving Prototypical Parts Abstraction for Case-Based Reasoning Explanations Designed for the Kidney Stone Type Recognition](https://arxiv.org/abs/2409.12883),因为有READme引用而自动导入该paper到Daily Paper,变成arxiv和HF都有的论文
- 仅来源于arxiv,完整输入arxiv链接的论文:[Aharonov-Bohm effects on the GUP framework](https://arxiv.org/abs/2410.11888),会因为有READme引用而自动导入该paper到Daily Paper
- 仅来源于arxiv,仅输入编号的论文:2409.00821
- 仅来源于arxiv,仅输入标题的论文:An Augmentation-based Model Re-adaptation Framework for Robust Image Segmentation
- 非arxiv论文:
@inproceedings{DBLP:conf/nips/XuLCLQ21,
author={Yong Xu and Feng Li and Zhile Chen and Jinxiu Liang and Yuhui Quan},
title={Encoding Spatial Distribution of Convolutional Features for Texture Representation},
year={2021},
cdate={1609459200000},
pages={22732-22744},
url={https://proceedings.neurips.cc/paper/2021/hash/c04c19c2c2474dbf5f7ac4372c5b9af1-Abstract.html},
booktitle={NeurIPS},
crossref={conf/nips/2021}
}
> 数据集标题record:allenai/WildBench
> 模型标题record:==black-forest-labs/FLUX.1-dev==
> 数据集标题record:LLM360/TxT360 sasad