#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
Bitcoin ETFs See Major Inflow Reversal
On January 15, Bitcoin spot ETFs recorded a net inflow of $755 million, marking the first inflow after four days of outflows. The Fidelity ETF (FBTC) led the charge, attracting $463 million. Meanwhile, Ethereum products also saw inflows, totaling $59.78 million.
Forecasts from HashKey Group predict Bitcoin could hit $300,000 by 2025 and Ethereum $8,000, with overall market cap reaching $10 trillion. Analyst insights suggest the Litecoin ETF may be next for approval in the US.
For more details, visit the link.
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