Text Generation
Transformers
Safetensors
mistral
RolePlay
Role-Play-Pro
NPC
Mystical
Character-Based-Gaming
Custom-Vision
TextVision-Text
Vision-Text
TextVision-Vision
TextAudio-Text
TextAudio-Audio
mergekit
Merge
Mistral_Star
Mistral_Quiet
Mistral
Mixtral
Question-Answer
Token-Classification
Sequence-Classification
SpydazWeb-AI
chemistry
biology
legal
code
climate
medical
LCARS_AI_StarTrek_Computer
text-generation-inference
chain-of-thought
tree-of-knowledge
forest-of-thoughts
visual-spacial-sketchpad
alpha-mind
knowledge-graph
entity-detection
encyclopedia
wikipedia
stack-exchange
Reddit
Cyber-series
MegaMind
Cybertron
SpydazWeb
Spydaz
LCARS
star-trek
mega-transformers
Mulit-Mega-Merge
Multi-Lingual
Afro-Centric
African-Model
Ancient-One
image-detection
Base64-Text
Text-Base64
Spectrogram-Text
Text-Spectrogram
Mel-Text
Text-Mel
Eval Results (legacy)
Instructions to use LeroyDyer/SpydazWeb_AI_HumanAI_RP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LeroyDyer/SpydazWeb_AI_HumanAI_RP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="LeroyDyer/SpydazWeb_AI_HumanAI_RP")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("LeroyDyer/SpydazWeb_AI_HumanAI_RP") model = AutoModelForCausalLM.from_pretrained("LeroyDyer/SpydazWeb_AI_HumanAI_RP") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use LeroyDyer/SpydazWeb_AI_HumanAI_RP with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "LeroyDyer/SpydazWeb_AI_HumanAI_RP" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LeroyDyer/SpydazWeb_AI_HumanAI_RP", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/LeroyDyer/SpydazWeb_AI_HumanAI_RP
- SGLang
How to use LeroyDyer/SpydazWeb_AI_HumanAI_RP 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 "LeroyDyer/SpydazWeb_AI_HumanAI_RP" \ --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": "LeroyDyer/SpydazWeb_AI_HumanAI_RP", "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 "LeroyDyer/SpydazWeb_AI_HumanAI_RP" \ --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": "LeroyDyer/SpydazWeb_AI_HumanAI_RP", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use LeroyDyer/SpydazWeb_AI_HumanAI_RP with Docker Model Runner:
docker model run hf.co/LeroyDyer/SpydazWeb_AI_HumanAI_RP
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