Text Generation
Transformers
PEFT
English
crn
cognitive-architecture
reasoning
adapter
gemma
gemma-4
CRN
cognitive-resonance-network
parameter-efficient
parameter-efficient-finetuning
hidden-state-correction
resonance-attention
episodic-memory
llm-adapter
tiny-model
efficient-inference
cpu-training
mac-m4
open-weights
experimental
research
Instructions to use eulogik/prajna with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eulogik/prajna with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="eulogik/prajna")# Load model directly from transformers import PrajnaStudentMultiLayer model = PrajnaStudentMultiLayer.from_pretrained("eulogik/prajna", dtype="auto") - PEFT
How to use eulogik/prajna with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use eulogik/prajna with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "eulogik/prajna" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "eulogik/prajna", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/eulogik/prajna
- SGLang
How to use eulogik/prajna 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 "eulogik/prajna" \ --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": "eulogik/prajna", "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 "eulogik/prajna" \ --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": "eulogik/prajna", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use eulogik/prajna with Docker Model Runner:
docker model run hf.co/eulogik/prajna
Prajna CRN — honest experiment: what it does and does NOT do
#1 opened 3 days ago
by
GautamKishore