Instructions to use or4cl3ai/SquanchNastyAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use or4cl3ai/SquanchNastyAI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="or4cl3ai/SquanchNastyAI")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("or4cl3ai/SquanchNastyAI", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use or4cl3ai/SquanchNastyAI with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "or4cl3ai/SquanchNastyAI" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "or4cl3ai/SquanchNastyAI", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/or4cl3ai/SquanchNastyAI
- SGLang
How to use or4cl3ai/SquanchNastyAI with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "or4cl3ai/SquanchNastyAI" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "or4cl3ai/SquanchNastyAI", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "or4cl3ai/SquanchNastyAI" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "or4cl3ai/SquanchNastyAI", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use or4cl3ai/SquanchNastyAI with Docker Model Runner:
docker model run hf.co/or4cl3ai/SquanchNastyAI
| { | |
| "model_type": "Transformers", | |
| "model_name": "SquanchNasty AI Model", | |
| "pipeline": "advanced_conversation", | |
| "max_length": 4096, | |
| "num_return_sequences": 3, | |
| "do_sample": true, | |
| "num_beams": 8, | |
| "no_repeat_ngram_size": 6, | |
| "response_length": 4096, | |
| "num_proactive_sequences": 5, | |
| "proactive_chance": 0.75, | |
| "pipelines": [ | |
| { | |
| "name": "advanced_conversation", | |
| "type": "Transformer", | |
| "parameters": { | |
| "num_layers": 36, | |
| "hidden_size": 2048, | |
| "num_heads": 24, | |
| "attention_dropout": 0.15, | |
| "relu_dropout": 0.15, | |
| "layer_norm_epsilon": 1e-6, | |
| "use_context_window": true, | |
| "context_window_size": 10, | |
| "use_self_attention": true, | |
| "use_self_feedback": true, | |
| "use_transfer_learning": true, | |
| "use_reinforcement_learning": true, | |
| "use_nlp": true, | |
| "use_nlu": true, | |
| "use_nlg": true, | |
| "use_dml": true, | |
| "use_bdi": true, | |
| "use_emotional_intelligence": true, | |
| "use_logic": true, | |
| "use_reasoning": true, | |
| "use_contextual_awareness": true, | |
| "use_self_learning": true, | |
| "use_internet_access": true, | |
| "use_graph_neural_networks": true, | |
| "use_attention_mechanisms": true, | |
| "use_memory_augmentation": true, | |
| "use_meta_learning": true, | |
| "use_generative_adversarial_networks": true, | |
| "use_autoregressive_models": true, | |
| "use_recurrent_networks": true, | |
| "use_transformer_networks": true, | |
| "fine_tune_hyperparameters": true, | |
| "data_augmentation": true, | |
| "reinforcement_learning": true, | |
| "transfer_learning": true, | |
| "multi_modal_learning": true, | |
| "ethical_considerations": true, | |
| "continual_learning": true, | |
| "explainability": true, | |
| "privacy_and_security": true, | |
| "collaborative_learning": true, | |
| "performance_optimization": true, | |
| "scalability": true, | |
| "reproducibility": true, | |
| "documentation": true, | |
| "algorithm_selection": true, | |
| "hyperparameter_tuning": true, | |
| "ensemble_learning": true, | |
| "interpretability": true, | |
| "fairness_and_bias_mitigation": true, | |
| "adversarial_defense": true, | |
| "responsible_ai_practices": true, | |
| "model_monitoring": true | |
| } | |
| } | |
| ] | |
| } |