#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
#ENS is rebounding from the support trendline of the descending channel, with the Ichimoku Cloud acting as a resistance barrier.
A decisive breakout above both the channel and the cloud would confirm bullish momentum.
#ENS/USDT analysis :
#ENS is currently in an uptrend, consistently reaching new highs while trading above the 200 EMA. The price is now retracing towards the 200 EMA and a significant support level. It is expected that the price will test this zone and rebound, which should support the continuation of bullish momentum and will lead to a retest of previous highs.
TF : 1D
Entry : $30.35
Target : $47
SL : $23.38
#ENS/USDT analysis :
#ENS is currently in an uptrend, trading above the 200 EMA. The price has recently bounced back from the 200 EMA, suggesting a continuation of its bullish momentum and potential testing of higher levels. For a long entry, it is advisable to wait for a retracement to optimize the entry point.
TF : 30min
Entry : $43
Target : $48
SL : $38