Replete-Adapted-llama3-8b 是一种通用模型,特别在超过100种编程语言中进行了编码训练。

8B

88 拉取 更新于6周前

6周前

版本d8c4bf3ef73d · 6.6GB

model
llama
·
8.03B
·
Q6_K
license
META LLAMA 3 COMMUNITY LICENSE AGREEMENT Meta Llama 3 Version Release Date: April 18, 2024 “Agreement” means the terms and conditions for use, reproduction, distribution and modification of the Llama Materials set forth herein. “Documentation” means the specifications, manuals and documentation accompanying Meta Llama 3 distributed by Meta at https://llama.meta.com/get-started/. “Licensee” or “you” means you, or your employer or any other person or entity (if you are entering into this Agreement on such person or entity’s behalf), of the age required under applicable laws, rules or regulations to provide legal consent and that has legal authority to bind your employer or such other person or entity if you are entering in this Agreement on their behalf. “Meta Llama 3” means the foundational large language models and software and algorithms, including machine-learning model code, trained model weights, inference-enabling code, training-enabling code, fine-tuning enabling code and other elements of the foregoing distributed by Meta at https://llama.meta.com/llama-downloads. “Llama Materials” means, collectively, Meta’s proprietary Meta Llama 3 and Documentation (and any portion thereof) made available under this Agreement. “Meta” or “we” means Meta Platforms Ireland Limited (if you are located in or, if you are an entity, your principal place of business is in the EEA or Switzerland) and Meta Platforms, Inc. 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template
{{ if .System }}<|start_header_id|>system<|end_header_id|> {{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|> {{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|> {{ .Response }}<|eot_id|>
params
{"num_keep":24,"stop":["<|start_header_id|>","<|end_header_id|>","<|eot_id|>"]}

README

Replete-AI/Llama3-8B-Instruct-Replete-Adapted

  • fp32量化
  • 使用 i-matrix calibration_datav3.txt
  • 强烈推荐使用 fp16 版本或更少量化的版本运行;该模型在 q4_0 上已经是随机不规律的。

Replete-Coder-llama3-8b

由 Rombodawg 微调

不仅仅是编码模型!

尽管 Replete-Coder 拥有惊人的编码能力,但它是基于大量非编码数据进行训练的,且经过了完全清洗和无审查。不要仅仅用它进行编码,用于所有需求吧!我们真正致力于打造 GPT 杀手!
image/png

感谢 TensorDock 赞助 Replete-Coder-llama3-8b 和 Replete-Coder-Qwen2-1.5b
您可以查看以下云计算租赁的网站。
- https://tensordock.com


Replete-Coder-llama3-8b 是一个通用模型,专门在超过 100 种编程语言中进行编码训练。用于训练模型的数据包含 25% 的非编码指示数据,75% 的编码指示数据,总计约 3.9 条百万行,约合 10 亿个标记,或 7.27gb 的指令数据。用于训练本模型的 100% 数据是无审查的,然后在训练之前完全去重。

Replete-Coder 模型(包括 Replete-Coder-llama3-8b 和 Replete-Coder-Qwen2-1.5b)具有以下特性:

  • 在超过100种编程语言中具备高级编码能力
  • 高级代码翻译(语言间的翻译)
  • 安全和漏洞预防相关的编码能力
  • 通用用途
  • 无审查的使用
  • 函数调用
  • 高级数学应用
  • 适用于低端(8b)和移动(1.5b)平台

注意:Replete-Coder 系列模型在 8192 个标记的上下文中进行了微调。在此上下文窗口之外的性能不被保证。

image/png


以下是非编码指示数据的25%

以下是非编码特定指示数据的75%

这两个数据集被合并,创建了以下用于训练的最终数据集

### System:
{}

### Instruction:
{}

### Response:
{}

注意:系统提示因训练数据而异,但最常用的一个是

Below is an instruction that describes a task, Write a response that appropriately completes the request.

结束标记

<|endoftext|>

感谢社区对 Replete-AI/code_bagel_hermes-2.5 数据集的贡献。如果没有这么多的成员将他们的数据集免费和开源,这个惊人的 AI 模型就不可能实现。

特别感谢 Teknium 为 Open-Hermes-2.5 数据集,以及 jondurbin 为 bagel 数据集和代码_bagel 系列数据集的命名思路。您可以找到以下链接到他们的 huggingface 账户

再次特别感谢 unsloth 作为 Replete-Coder 的主要训练方法。以下您可以找到他们的 github,以及用于训练本模型的特殊 Replete-Ai 秘密酱(Unsloth + Qlora + Galore)colab 代码文档。