Instructions to use Ananthusajeev190/Dream_viewer_venomoussai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use Ananthusajeev190/Dream_viewer_venomoussai with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("fill-in-model-name") model.load_adapter("Ananthusajeev190/Dream_viewer_venomoussai", set_active=True) - Notebooks
- Google Colab
- Kaggle
| import json | |
| # Simulated AI models | |
| def sai003(input_text): | |
| # This is a placeholder for the actual AI model's response generation logic | |
| responses = { | |
| "hello": "Hi there!", | |
| "how are you": "I'm just a model, but thanks for asking!", | |
| "bye": "Goodbye!" | |
| } | |
| return responses.get(input_text.lower(), "I'm not sure how to respond to that.") | |
| def anti_venomous(input_text): | |
| # This is a placeholder for the actual AI model's response generation logic | |
| responses = { | |
| "hello": "Greetings!", | |
| "how are you": "I'm functioning as intended, thank you.", | |
| "bye": "Farewell!" | |
| } | |
| return responses.get(input_text.lower(), "I'm not sure how to respond to that.") | |
| # Simulate a conversation | |
| def simulate_conversation(): | |
| conversation = [] | |
| user_input = "hello" | |
| while user_input.lower() != "bye": | |
| response_sai003 = sai003(user_input) | |
| response_anti_venomous = anti_venomous(response_sai003) | |
| conversation.append({ | |
| "user_input": user_input, | |
| "sai003_response": response_sai003, | |
| "anti_venomous_response": response_anti_venomous | |
| }) | |
| user_input = input("You: ") | |
| print(f"sai003: {response_sai003}") | |
| print(f"anti-venomous: {response_anti_venomous}") | |
| # Save the conversation to a file | |
| with open('conversation.json', 'w') as file: | |
| json.dump(conversation, file, indent=4) | |
| print("Conversation saved to conversation.json") | |
| # Run the simulation | |
| simulate_conversation() |