Model Details ? The 1st Place Solution to The 8th NVIDIA AI City Challenge (2024) Track 2: CityLLaVA
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Llama-3-Chinese-8B-LoRA 这个仓库包含了Llama-3-Chinese-8B-LoRA,它是在Meta-Llama-3-8B的基础上,使用了120GB的中文文本语料
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Llama-3-Chinese-8B-GGUF 提醒: GGUF文件已重新生成,由于llama.cpp仍然有可能对其作出修改,因此建议保留HF版模型。 这个仓库包含了Llama-3-Ch
270other
[![Generic badge](https://img.shields.io/badge/GitHub-%20XTuner-black.svg)](https://github.com/Inter
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[![Generic badge](https://img.shields.io/badge/GitHub-%20XTuner-black.svg)](https://github.com/Inter
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[![Generic badge](https://img.shields.io/badge/GitHub-%20XTuner-black.svg)](https://github.com/Inter
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[![Generic badge](https://img.shields.io/badge/GitHub-%20XTuner-black.svg)](https://github.com/Inter
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PALM文本生成模型介绍 PALM模型是一个通用的预训练生成模型,可以用于解决下游各种类型的生成任务。模型利用大量无监督数据,通过结合自编码和自回归任务进行预训练。可以用于解决文本生成相关的任务包含:
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Chinese-Mixtral-Instruct Chinese Mixtral GitHub repository: https://github.com/ymcui/Chinese-
270moe
Chinese-Mixtral-Instruct-LoRA Chinese Mixtral GitHub repository: https://github.com/ymcui/Chi
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Chinese-Mixtral-LoRA Chinese Mixtral GitHub repository: https://github.com/ymcui/Chinese-Mixt
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Chinese-Mixtral Chinese Mixtral GitHub repository: https://github.com/ymcui/Chinese-Mixtral T
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Llama-3-Chinese-8B 这个仓库包含了Llama-3-Chinese-8B,它是在Meta-Llama-3-8B的基础上,使用了120GB的中文文本语料进行进一步预训练。
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JetMoE: Reaching LLaMA2 Performance with 0.1M Dollars Key Messages JetMoE-8B is trained with less t
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StructBERT中文情感分类模型介绍 情感分类任务,通常为输入一段句子或一段话,返回该段话正向/负向的情感极性,在用户评价,观点抽取,意图识别中往往起到重要作用。StructBERT中文情感分类模
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[![Generic badge](https://img.shields.io/badge/GitHub-%20XTuner-black.svg)](https://github.com/Inter
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[![Generic badge](https://img.shields.io/badge/GitHub-%20XTuner-black.svg)](https://github.com/Inter
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Llama-3-8B-Agent This Adapter is fine-tune from meta-llama/Meta-Llama-3-8B-Instruct using LLaMA-Fact
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Llama-3-8B-Agent This Adapter is fine-tune from meta-llama/Meta-Llama-3-8B-Instruct using LLaMA-Fact
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# EmoLLM-心理健康大模型 [![Contributors][contributors-shield]][contributors-url] [![Forks]
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