Instructions to use FashGate/config with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FashGate/config with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("FashGate/config", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update zh_CN.json
Browse files- zh_CN.json +1 -1
zh_CN.json
CHANGED
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@@ -573,7 +573,7 @@
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| 573 |
"How many results to load at once": "单次加载的结果数量",
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| 574 |
"How often, in seconds, to flush the pending tensorboard events and summaries to disk.": "将挂起的 tensorboard 事件和摘要刷新到磁盘的频率 (单位:秒)",
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| 575 |
"HuggingFace Token": "HuggingFace 令牌(Token)",
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| 576 |
-
"Hypernetwork": "
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| 577 |
"Hypernetwork Learning rate": "超网络学习率",
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| 578 |
"Hypernetwork strengths": "超网络强度",
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| 579 |
"Hypernetworks": "超网络(Hypernetwork)",
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| 573 |
"How many results to load at once": "单次加载的结果数量",
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| 574 |
"How often, in seconds, to flush the pending tensorboard events and summaries to disk.": "将挂起的 tensorboard 事件和摘要刷新到磁盘的频率 (单位:秒)",
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| 575 |
"HuggingFace Token": "HuggingFace 令牌(Token)",
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| 576 |
+
"Hypernetwork": "Hypernetwork",
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| 577 |
"Hypernetwork Learning rate": "超网络学习率",
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| 578 |
"Hypernetwork strengths": "超网络强度",
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| 579 |
"Hypernetworks": "超网络(Hypernetwork)",
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