diff --git a/README.md b/README.md
index 6b07022..1194b4d 100644
--- a/README.md
+++ b/README.md
@@ -1,3 +1,94 @@
-# Atom-7B-Chat_a13650745442299904330981
+---
+license: Apache License 2.0
+---
+### Clone with HTTP
+```bash
+git clone https://www.modelscope.cn/FlagAlpha/Atom-7B-Chat.git
+```
+
+# Atom-7B-Chat
+
+Atom-7B-Chat基于Atom-7B的对话模型，完全开源可商用，由Llama中文社区和AtomEcho（原子回声）联合研发，我们会持续提供更新的模型参数，模型训练过程见[llama.family](https://llama.family)。
+
+模型的部署、训练、微调等方法详见Llama中文社区GitHub仓库：[**Llama2-Chinese**](https://github.com/FlagAlpha/Llama2-Chinese)。
+
+## 📝 中文数据
+
+| 类型 | 描述 |
+| ---------------------------------------------------------- | ------------------------------------------------------------ |
+| 网络数据 | 互联网上公开的网络数据，挑选出去重后的高质量中文数据，涉及到百科、书籍、博客、新闻、公告、小说等高质量长文本数据。 |
+| [Wikipedia](https://github.com/goldsmith/Wikipedia) | 中文Wikipedia的数据 |
+| [悟道](https://github.com/BAAI-WuDao/Model) | 中文悟道开源的200G数据 |
+| [Clue](https://github.com/CLUEbenchmark/CLUEDatasetSearch) | Clue开放的中文预训练数据，进行清洗后的高质量中文长文本数据 |
+| 竞赛数据集 | 近年来中文自然语言处理多任务竞赛数据集，约150个 |
+| [MNBVC](https://github.com/esbatmop/MNBVC) | MNBVC 中清洗出来的部分数据集 |
+
+**我们也欢迎大家在[llama.family](https://llama.family)中贡献自己的数据，您的数据通过审核后会加入模型训练，也将影响模型未来的能力走向。**
+
+
+## 📚 中文词表
+
+为了提高中文文本处理的效率，我们针对Llama2模型的词表进行了深度优化。
+
+首先，我们基于数百G的中文文本，**在Llama2词表的基础上扩展词库至65,000个单词**。
+
+经过测试，我们的改进使得**中文编码/解码速度提高了约350％**。
+
+此外，我们还扩大了中文字符集的覆盖范围，包括所有**emoji符号**，这使的生成带有表情符号的文章更加高效。
+
+对于Llama2原生词表中的一些特殊情况，如数字、英文等，我们尽可能地避免对其进行修改或替换。
+
+最终，成功地实现了一种既能提高中文处理效率又能保持Llama2原有性能的方法。
+
+
+## 📈 训练过程
+
+**模型结构**
+
+基于当前最优秀的开源模型Llama2，使用主流Decoder-only的标准Transformer网络结构，支持4K的上下文长度（Context Length），为同尺寸模型中最长，能满足更长的多轮对话、知识问答与摘要等需求，模型应用场景更广泛。
+
+**FlashAttention-2高效训练**
+
+Atom-7B采用了FlashAttention-2技术进行训练。由于在处理较长的输入序列时，内存消耗的问题可能会导致“内存爆炸”现象。FlashAttention-2是一种高效注意力机制的实现方式之一，相较于传统的注意力技术（Attention），它拥有更快速的速度以及更加优化的内存占用率。
+
+**基于NTK的自适应上下文扩展技术**
+
+- 可在不继续训练模型的情况下支持更长的上下文
+- 本项目中模型默认支持4K上下文，利用上述技术可扩展至18K+
+- 经过微调可以支持到32K+
+
+
+## 💻 推理配置
+实际应用中，消费级显卡要比专业显卡便宜的多（比如3090相比A10，同样都是24G显存）。
+
+对于消费级显卡，直接FP32肯定放不下，一般最基本的是FP16，而INT8和INT4量化就很有用，例如：
+
+- 对于3080显卡（10G显存），Atom-7B的INT8只需要8G显存可以直接部署。
+- 对于3080显卡（10G显存），Atom-7B的INT4只需要5G显存可以直接部署。
+
+
+---
+
+
+# Llama中文社区
+
+## 🚀 社区地址：
+
+Github：[**Llama2-Chinese**](https://github.com/FlagAlpha/Llama2-Chinese)
+
+在线体验链接：[**llama.family**](https://llama.family/)
+
+## 🔥 社区介绍
+欢迎来到Llama中文社区！
+
+我们是一个专注于Llama模型在中文方面的优化和上层建设的高级技术社区。
+
+**基于大规模中文数据，从预训练开始对Llama2模型进行中文能力的持续迭代升级**。
+
+我们热忱欢迎对大模型LLM充满热情的开发者和研究者加入我们的行列。
+
+## 🐼 社区资源
+ - Llama2在线体验链接[**llama.family**](https://llama.family/)，同时包含Meta原版和中文微调版本！
+ - Llama2 Chat模型的[中文问答能力评测](https://github.com/FlagAlpha/Llama2-Chinese/tree/main#-%E6%A8%A1%E5%9E%8B%E8%AF%84%E6%B5%8B)！
+ - [社区飞书知识库](https://chinesellama.feishu.cn/wiki/space/7257824476874768388?ccm_open_type=lark_wiki_spaceLink)，欢迎大家一起共建！
-Atom-7B-Chat基于Atom-7B的32K长度的对话模型，由Llama中文社区和AtomEcho（原子回声）联合研发
\ No newline at end of file
diff --git a/config.json b/config.json
new file mode 100644
index 0000000..3a3671c
--- /dev/null
+++ b/config.json
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+{
+ "_name_or_path": "/mnt/data/zhangzheng/data/AtoM-7B/checkpoint-56000",
+ "architectures": [
+ "LlamaForCausalLM"
+ ],
+ "bos_token_id": 1,
+ "eos_token_id": 2,
+ "hidden_act": "silu",
+ "hidden_size": 4096,
+ "initializer_range": 0.02,
+ "intermediate_size": 11008,
+ "max_length": 4096,
+ "max_position_embeddings": 4096,
+ "model_type": "llama",
+ "num_attention_heads": 32,
+ "num_hidden_layers": 32,
+ "num_key_value_heads": 32,
+ "pad_token_id": 2,
+ "pretraining_tp": 1,
+ "rms_norm_eps": 1e-05,
+ "rope_scaling": null,
+ "tie_word_embeddings": false,
+ "torch_dtype": "float16",
+ "transformers_version": "4.31.0",
+ "use_cache": true,
+ "vocab_size": 65000
+}
diff --git a/configuration.json b/configuration.json
new file mode 100644
index 0000000..ae67ce8
--- /dev/null
+++ b/configuration.json
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+{
+ "framework": "pytorch",
+ "task": "text-generation",
+ "model": {
+ "type": "Atom-7B-Chat"
+ },
+ "pipeline": {
+ "type": "Atom-7B-Chat-pipe"
+ },
+ "allow_remote": true
+}
diff --git a/generation_config.json b/generation_config.json
new file mode 100644
index 0000000..afb9791
--- /dev/null
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+{
+ "_from_model_config": true,
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+ "eos_token_id": 2,
+ "max_length": 4096,
+ "pad_token_id": 2,
+ "transformers_version": "4.31.0"
+}
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+ "tokenizer_class": "LlamaTokenizer",
+ "unk_token": {
+ "__type": "AddedToken",
+ "content": "",
+ "lstrip": false,
+ "normalized": true,
+ "rstrip": false,
+ "single_word": false
+ }
+}