Quantization
Collection
A collection of quantized models. All the models can be fine-tuned by adding a LoRA Adapter. • 82 items • Updated • 3
How to use shuyuej/gemma-2-27b-GPTQ with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="shuyuej/gemma-2-27b-GPTQ") # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("shuyuej/gemma-2-27b-GPTQ")
model = AutoModelForCausalLM.from_pretrained("shuyuej/gemma-2-27b-GPTQ")How to use shuyuej/gemma-2-27b-GPTQ with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "shuyuej/gemma-2-27b-GPTQ"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "shuyuej/gemma-2-27b-GPTQ",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'docker model run hf.co/shuyuej/gemma-2-27b-GPTQ
How to use shuyuej/gemma-2-27b-GPTQ with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "shuyuej/gemma-2-27b-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": "shuyuej/gemma-2-27b-GPTQ",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'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 "shuyuej/gemma-2-27b-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": "shuyuej/gemma-2-27b-GPTQ",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'How to use shuyuej/gemma-2-27b-GPTQ with Docker Model Runner:
docker model run hf.co/shuyuej/gemma-2-27b-GPTQ
Original Base Model: google/gemma-2-27b.
Link: https://huggingface.co/google/gemma-2-27b
"quantization_config": {
"bits": 4,
"checkpoint_format": "gptq",
"damp_percent": 0.1,
"desc_act": true,
"group_size": 128,
"model_file_base_name": null,
"model_name_or_path": null,
"quant_method": "gptq",
"static_groups": false,
"sym": true,
"true_sequential": true
},
Source Codes: https://github.com/vkola-lab/medpodgpt/tree/main/quantization.