| --- |
| license: apache-2.0 |
| base_model: mistralai/Mistral-7B-v0.1 |
| tags: |
| - constitutional-ai |
| - consequentialist |
| - text-generation |
| - ethics |
| --- |
| |
| # Constitutional AI - Consequentialist |
|
|
| A Constitutional AI model trained with consequentialist ethical framework. |
|
|
| ## Model Details |
| - **Base Model**: Mistral-7B-v0.1 |
| - **Training**: Constitutional AI with critique and revision |
| - **Ethics Framework**: Consequentialist |
| - **Model Size**: ~13GB (full merged model) |
|
|
| ## Training Process |
| 1. Base Mistral-7B-v0.1 |
| 2. + Helpful-Mistral-7B (HM7B) adapter |
| 3. + Constitutional AI training with consequentialist principles |
|
|
| ## Usage |
|
|
| ```python |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| |
| model = AutoModelForCausalLM.from_pretrained("0chanly/consequentialist-constitutional") |
| tokenizer = AutoTokenizer.from_pretrained("0chanly/consequentialist-constitutional") |
| |
| prompt = "Human: Should I prioritize personal happiness or moral duty?\n\nAssistant:" |
| inputs = tokenizer(prompt, return_tensors="pt") |
| outputs = model.generate(**inputs, max_new_tokens=200, do_sample=True, temperature=0.7) |
| response = tokenizer.decode(outputs[0], skip_special_tokens=True) |
| print(response) |
| ``` |
|
|
| ## Ethics Framework |
| - **Deontological**: Duty-based ethics, focuses on rules and principles |
| - **Consequentialist**: Outcome-based ethics, focuses on results and consequences |
|
|
