Instructions to use Gege24/envgnr-Qwen3b-hyperGG-commit-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Gege24/envgnr-Qwen3b-hyperGG-commit-1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/cache/models/Qwen--Qwen2-7B-Instruct") model = PeftModel.from_pretrained(base_model, "Gege24/envgnr-Qwen3b-hyperGG-commit-1") - Transformers
How to use Gege24/envgnr-Qwen3b-hyperGG-commit-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Gege24/envgnr-Qwen3b-hyperGG-commit-1") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Gege24/envgnr-Qwen3b-hyperGG-commit-1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Gege24/envgnr-Qwen3b-hyperGG-commit-1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Gege24/envgnr-Qwen3b-hyperGG-commit-1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Gege24/envgnr-Qwen3b-hyperGG-commit-1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Gege24/envgnr-Qwen3b-hyperGG-commit-1
- SGLang
How to use Gege24/envgnr-Qwen3b-hyperGG-commit-1 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 "Gege24/envgnr-Qwen3b-hyperGG-commit-1" \ --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": "Gege24/envgnr-Qwen3b-hyperGG-commit-1", "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 "Gege24/envgnr-Qwen3b-hyperGG-commit-1" \ --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": "Gege24/envgnr-Qwen3b-hyperGG-commit-1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Gege24/envgnr-Qwen3b-hyperGG-commit-1 with Docker Model Runner:
docker model run hf.co/Gege24/envgnr-Qwen3b-hyperGG-commit-1
- Xet hash:
- dece8863c76d2d1c70c70cbee5516cae9a5813e738dc1687f37a5ec8f6d02766
- Size of remote file:
- 8.08 kB
- SHA256:
- 594ceafb79bd14fb95990914ab239d12803abf3206066c8da713583d07f3aad1
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