Text Generation
Safetensors
GGUF
English
reasoning
reinforcement-learning
grpo
small-language-model
samsung-ennovatex
conversational
Instructions to use OmnipotentFool/Aurvion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use OmnipotentFool/Aurvion with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf OmnipotentFool/Aurvion:Q4_K_M # Run inference directly in the terminal: llama cli -hf OmnipotentFool/Aurvion:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf OmnipotentFool/Aurvion:Q4_K_M # Run inference directly in the terminal: llama cli -hf OmnipotentFool/Aurvion:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf OmnipotentFool/Aurvion:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf OmnipotentFool/Aurvion:Q4_K_M
Use Docker
docker model run hf.co/OmnipotentFool/Aurvion:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use OmnipotentFool/Aurvion with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OmnipotentFool/Aurvion" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OmnipotentFool/Aurvion", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/OmnipotentFool/Aurvion:Q4_K_M
- Ollama
How to use OmnipotentFool/Aurvion with Ollama:
ollama run hf.co/OmnipotentFool/Aurvion:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use OmnipotentFool/Aurvion with Docker Model Runner:
docker model run hf.co/OmnipotentFool/Aurvion:Q4_K_M
- Lemonade
How to use OmnipotentFool/Aurvion with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull OmnipotentFool/Aurvion:Q4_K_M
Run and chat with the model
lemonade run user.Aurvion-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download llama.cpp/ggml/src/ggml-virtgpu/virtgpu-forward-impl.h from OmnipotentFool/Aurvion: direct link, hf CLI and curl.
- Browser
- Download file 2.9 kB
-
https://huggingface.co/OmnipotentFool/Aurvion/resolve/main/llama.cpp/ggml/src/ggml-virtgpu/virtgpu-forward-impl.h
- Command line
-
hf download hf://OmnipotentFool/Aurvion/llama.cpp/ggml/src/ggml-virtgpu/virtgpu-forward-impl.h
-
curl -L -o virtgpu-forward-impl.h https://huggingface.co/OmnipotentFool/Aurvion/resolve/main/llama.cpp/ggml/src/ggml-virtgpu/virtgpu-forward-impl.h
2.9 kB
| // clang-format off | |
| // clang-format on | |
| int32_t REMOTE_CALL_PREPARE_forward_flag = (int32_t) apir_command_type__; \ | |
| const char * REMOTE_CALL_PREPARE_command_name = apir_dispatch_command_name(apir_command_type__); \ | |
| do { \ | |
| encoder_name = remote_call_prepare(gpu_dev_name, APIR_COMMAND_TYPE_FORWARD, REMOTE_CALL_PREPARE_forward_flag); \ | |
| if (!encoder_name) { \ | |
| GGML_ABORT(GGML_VIRTGPU "%s: failed to prepare the remote call encoder", __func__); \ | |
| } \ | |
| } while (0) | |
| do { \ | |
| ret_name = (ApirForwardReturnCode) remote_call(gpu_dev_name, encoder_name, &decoder_name, 0, NULL); \ | |
| if (!decoder_name) { \ | |
| GGML_ABORT(GGML_VIRTGPU "%s: failed to kick the remote call", __func__); \ | |
| } \ | |
| if (ret_name < APIR_FORWARD_BASE_INDEX) { \ | |
| GGML_ABORT(GGML_VIRTGPU "%s: failed to forward the API call: %s: code %d", __func__, \ | |
| apir_forward_error(ret_name), ret_name); \ | |
| } \ | |
| ret_name = (ApirForwardReturnCode) (ret_name - APIR_FORWARD_BASE_INDEX); \ | |
| if (ret_name != 0) { \ | |
| GGML_ABORT(GGML_VIRTGPU "backend function '%s' failed (return code: %d)", \ | |
| REMOTE_CALL_PREPARE_command_name, ret_name); \ | |
| } \ | |
| } while (0) | |