Text Generation
Transformers
PyTorch
prajna-crn
prajna-v2
cehri
licensing-exam
exam-passing
cognitive-resonance-network
crn
memory-augmented-generation
retrieval-augmented
small-language-model
adapter
efficient-ai
edge-ai
on-device-ai
fine-tuning
gemma
question-answering
facts
arithmetic
implicit-goal-reasoning
Eval Results (legacy)
Instructions to use eulogik/Prajna-V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eulogik/Prajna-V2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="eulogik/Prajna-V2")# Load model directly from transformers import PrajnaStudentMultiLayer model = PrajnaStudentMultiLayer.from_pretrained("eulogik/Prajna-V2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use eulogik/Prajna-V2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "eulogik/Prajna-V2" # 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-V2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/eulogik/Prajna-V2
- SGLang
How to use eulogik/Prajna-V2 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-V2" \ --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-V2", "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-V2" \ --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-V2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use eulogik/Prajna-V2 with Docker Model Runner:
docker model run hf.co/eulogik/Prajna-V2
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