Text Generation
Transformers
PyTorch
JAX
Russian
gpt2
PyTorch
Transformers
text-generation-inference
Instructions to use Gnider/model_old_working with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gnider/model_old_working with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Gnider/model_old_working")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Gnider/model_old_working") model = AutoModelForCausalLM.from_pretrained("Gnider/model_old_working") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Gnider/model_old_working with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Gnider/model_old_working" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Gnider/model_old_working", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Gnider/model_old_working
- SGLang
How to use Gnider/model_old_working 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 "Gnider/model_old_working" \ --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": "Gnider/model_old_working", "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 "Gnider/model_old_working" \ --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": "Gnider/model_old_working", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Gnider/model_old_working with Docker Model Runner:
docker model run hf.co/Gnider/model_old_working
- Xet hash:
- 9071e474490f65ddfb2251b0af8dd6d6cff8adc2ad97511516158088bafc118c
- Size of remote file:
- 551 MB
- SHA256:
- 0d2a4a387b0430654bb1f6813436bd31f8e10a06e18ea0e5c41b33120b78458e
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