With the cost of a cup of Starbucks and two hours of your time, you can own your own trained open-source large-scale model.
As we see it, the Alpaca guys’ main contribution was to show that it’s relatively easy to train a model to follow instructions. For context, the most popular chatbot is ChatGPT from OpenAI. OpenAI really sold the so-called RLHF, reinforcement learning from human feedback, as a method ...
In this guide, we’ll walk you through the simple steps to add a ChatGPT-powered chatbot to your website and easily train it on your own data. With just a few clicks, anyone in your organization can train the chatbot by adding the URL's for your website or knowledge base - no...
When we say "train" here, we mean giving ChatGPT extra context with your prompt or knowledge sources so that it can consider your information when responding back. This is separate from another type of advanced AI training—and a different discussion altogether—called "model training" where inf...
Model training: I'm developing a machine learning model for [specific task/problem]. Act as a machine learning engineer specializing in [relevant field]. Help me train a [model name] by providing Python code to tune the hyperparameters and predict [parameters]. Include comments explaining each...
How to train ChatGPT on your own data The best ChatGPT alternatives How to use ChatGPT canvas What is ChatGPT Pro—and is it worth it? What are Claude computer use and OpenAI Operator? Use ChatGPT (OpenAI) MCP to take action in your AI tools This article was originally published in ...
MedicalGPT: Training Your Own Medical GPT Model with ChatGPT Training Pipeline. 训练医疗大模型,实现了包括增量预训练、有监督微调、RLHF(奖励建模、强化学习训练)和DPO(直接偏好优化)。 - anthonyyuan/MedicalGPT
MedicalGPT: Training Your Own Medical GPT Model with ChatGPT Training Pipeline. 训练医疗大模型,实现了包括增量预训练(PT)、有监督微调(SFT)、RLHF、DPO、ORPO、GRPO。 - shibing624/MedicalGPT
https://medium.com/analytics-vidhya/a-comprehensive-guide-to-build-your-own-language-model-in-python-5141b3917d6d 到这里为止可以说NLP-DL的“上一个时代”就结束了,因为后面出现的就是GPT和BERT系列的工作,他们会用到很多之前就提出的idea,主流的工作也是BERT的变种、trans的变种、bert的新应用。还有轻量...
# 导入必要的库 import pandas as pd from sklearn.model_selection import train_test_split from sklearn.tree import DecisionTreeClassifier from sklearn.metrics import accuracy_score # 创建虚拟数据集 data = { '硬度': [60, 70, 65, 55, 75, 80, 85, 90, 95, 100], '重量': [100, 120, ...