#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
#RAD/USDT analysis :
#RAD is currently experiencing a bearish trend, trading below the 200 EMA. The price is forming lower lows (LLs) and lower highs (LHs).
At present, it is testing the resistance zone along with the 200 EMA. A reversal is anticipated from this level, allowing the price to resume its bearish momentum and potentially test lower levels.
TF : 1H
Entry : $0.840
Target : $0.779
SL : $0.875
#RAD/USDT analysis :
#RAD has broken out and retested the previous support levels. It is expected to reject from the current level and test lower levels.
TF : 1h
Entry : $1.209
Target : $1.127
SL : $1.268