Instructions to use FPHam/ProfMcSmartyBS_13b_GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FPHam/ProfMcSmartyBS_13b_GPTQ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="FPHam/ProfMcSmartyBS_13b_GPTQ")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("FPHam/ProfMcSmartyBS_13b_GPTQ") model = AutoModelForCausalLM.from_pretrained("FPHam/ProfMcSmartyBS_13b_GPTQ", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use FPHam/ProfMcSmartyBS_13b_GPTQ with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "FPHam/ProfMcSmartyBS_13b_GPTQ" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FPHam/ProfMcSmartyBS_13b_GPTQ", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/FPHam/ProfMcSmartyBS_13b_GPTQ
- SGLang
How to use FPHam/ProfMcSmartyBS_13b_GPTQ 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 "FPHam/ProfMcSmartyBS_13b_GPTQ" \ --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": "FPHam/ProfMcSmartyBS_13b_GPTQ", "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 "FPHam/ProfMcSmartyBS_13b_GPTQ" \ --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": "FPHam/ProfMcSmartyBS_13b_GPTQ", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use FPHam/ProfMcSmartyBS_13b_GPTQ with Docker Model Runner:
docker model run hf.co/FPHam/ProfMcSmartyBS_13b_GPTQ
Commit History
-
Update README.md
Verified signaturefa9d377
-
Update README.md
1da6a12 -
Update README.md
9d447d8 -
Update README.md
4db9b23 -
Update README.md
2dc26e2 -
Update README.md
210ef47 -
Update README.md
a6eb297 -
Update README.md
672f878 -
Update README.md
c993e9f -
Update README.md
d2aa14b -
Update README.md
74f14db -
Update README.md
02f1561 -
Update README.md
fb99ebc -
Update README.md
d963901 -
Update README.md
67b761d -
Upload smarty_bc.jpg
19f8a9b -
Delete smartybc.jpg
287775a -
Upload smartybc.jpg
cac5e18 -
Delete 00336-2527140576.png
6886b62 -
Upload 00336-2527140576.png
47097e7 -
Upload 8 files
71e08b9
-
Update README.md
388a8ae -
Create README.md
0f244ec -
initial commit
4275c29