Text Generation
Transformers
Safetensors
English
hardware
hardware-engineering
embedded-systems
electronics
pcb-design
verilog
vhdl
rtl
fpga
microcontroller
arm
risc-v
firmware
driver
linux-kernel
device-driver
bare-metal
rtos
circuit-design
analog
digital
power-electronics
bms
can-bus
i2c
spi
uart
dma
interrupt
bootloader
linker-script
assembly
c
cpp
python
qlora
4bit
bfloat16
hardware-expert
ornith
fine-tuned
Rust
Cuda
System-low-level-code
Cuda-expert
conversational
8-bit precision
Instructions to use fe-dev-dl/Ornith-1.0-9B-Hardware-Expert-fp16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fe-dev-dl/Ornith-1.0-9B-Hardware-Expert-fp16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="fe-dev-dl/Ornith-1.0-9B-Hardware-Expert-fp16") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fe-dev-dl/Ornith-1.0-9B-Hardware-Expert-fp16", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use fe-dev-dl/Ornith-1.0-9B-Hardware-Expert-fp16 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "fe-dev-dl/Ornith-1.0-9B-Hardware-Expert-fp16" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "fe-dev-dl/Ornith-1.0-9B-Hardware-Expert-fp16", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/fe-dev-dl/Ornith-1.0-9B-Hardware-Expert-fp16
- SGLang
How to use fe-dev-dl/Ornith-1.0-9B-Hardware-Expert-fp16 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 "fe-dev-dl/Ornith-1.0-9B-Hardware-Expert-fp16" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "fe-dev-dl/Ornith-1.0-9B-Hardware-Expert-fp16", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "fe-dev-dl/Ornith-1.0-9B-Hardware-Expert-fp16" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "fe-dev-dl/Ornith-1.0-9B-Hardware-Expert-fp16", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use fe-dev-dl/Ornith-1.0-9B-Hardware-Expert-fp16 with Docker Model Runner:
docker model run hf.co/fe-dev-dl/Ornith-1.0-9B-Hardware-Expert-fp16
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