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Source channel @githubtrending · Post #14815 · Jun 10

#jupyter_notebook#chatglm#chatglm3#gemma_2b_it#glm_4#internlm2#llama3#llm#lora#minicpm#q_wen#qwen#qwen1_5#qwen2 This guide helps beginners set up and use open-source large language models (LLMs) on Linux or cloud platforms like AutoDL, with step-by-step instructions for environment setup, model deployment, and fine-tuning for models such as LLaMA, ChatGLM, and InternLM[2][4][5]. It covers everything from basic installation to advanced techniques like LoRA and distributed fine-tuning, and supports integration with tools like LangChain and online demo deployment. The main benefit is making powerful AI models accessible and easy to use for students, researchers, and anyone interested in experimenting with or customizing LLMs for their own projects[2][4][5]. https://github.com/datawhalechina/self-llm

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Libreware

@libreware · Post #1330 · 09/05/2024, 08:53 PM

Interactive PDF Analysis (also called IPA) allows any researcher to explore the inner details of any PDF file. PDF files may be used to carry malicious payloads that exploit vulnerabilities, and issues of PDF viewer, or may be used in phishing campaigns as social engineering artefacts. The goal of this software is to let any analyst go deep on its own the PDF file. Via IPA, you may extract important payload from PDF files, understand the relationship across objects, and infer elements that may be helpful for triage of malicious or untrusted payloads. IPA/README.md at main · seekbytes/IPA · GitHub #PDF#PDFanalysis#Malware#Security