Text Generation
Transformers
PyTorch
ONNX
Russian
transformer
feature-extraction
chat
russian
easyformer
custom_code
conversational
Instructions to use OpenRussianAI/andrey with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenRussianAI/andrey with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="OpenRussianAI/andrey", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenRussianAI/andrey", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use OpenRussianAI/andrey with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OpenRussianAI/andrey" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenRussianAI/andrey", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/OpenRussianAI/andrey
- SGLang
How to use OpenRussianAI/andrey 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 "OpenRussianAI/andrey" \ --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": "OpenRussianAI/andrey", "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 "OpenRussianAI/andrey" \ --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": "OpenRussianAI/andrey", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use OpenRussianAI/andrey with Docker Model Runner:
docker model run hf.co/OpenRussianAI/andrey
File size: 436 Bytes
0e28380 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"vocab_size": 1172,
"d_model": 256,
"n_layer": 6,
"n_head": 4,
"ctx": 128,
"dropout": 0.3,
"architectures": [
"EasyFormerLMHeadModel"
],
"model_type": "transformer",
"auto_map": {
"AutoConfig": "configuration_easyformer.EasyFormerConfig",
"AutoModel": "modeling_easyformer.EasyFormerLMHeadModel",
"AutoModelForCausalLM": "modeling_easyformer.EasyFormerLMHeadModel"
},
"torch_dtype": "float32"
} |