Text Generation
Transformers
Safetensors
gemma3_text
Generated from Trainer
trl
dpo
hf_jobs
text-generation-inference
Instructions to use mrshu/grd-exp24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrshu/grd-exp24 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="mrshu/grd-exp24")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("mrshu/grd-exp24") model = AutoModelForCausalLM.from_pretrained("mrshu/grd-exp24") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use mrshu/grd-exp24 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "mrshu/grd-exp24" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mrshu/grd-exp24", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/mrshu/grd-exp24
- SGLang
How to use mrshu/grd-exp24 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 "mrshu/grd-exp24" \ --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": "mrshu/grd-exp24", "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 "mrshu/grd-exp24" \ --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": "mrshu/grd-exp24", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use mrshu/grd-exp24 with Docker Model Runner:
docker model run hf.co/mrshu/grd-exp24
- Xet hash:
- 076018ae60b515813cc678540dcf7df053f2c789b8905e95fb76005c0ec78d6b
- Size of remote file:
- 5.84 kB
- SHA256:
- 2b0786af164289e97cef2f1225a4fabf8d1ded4a18fc824e06a5f5945310fd08
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.