AWQ-quantized package (W4G128) of google/gemma-2-9b
.
Support for Gemma2 in the codebase of AutoAWQ is proposed in the following pull request.
To use the model, follow the AutoAWQ examples with the source from #562.
Evaluation
WikiText-2 PPL: 7.08
C4 PPL: 11.05
Loading
model_path = "radi-cho/gemma-2-9b-AWQ"
# With transformers
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained(model_path, device_map="cuda:0")
# With transformers (fused)
from transformers import AutoModelForCausalLM, AwqConfig
quantization_config = AwqConfig(bits=4, fuse_max_seq_len=512, do_fuse=True)
model = AutoModelForCausalLM.from_pretrained(model_path, quantization_config=quantization_config).to(0)
# With AutoAWQ
from awq import AutoAWQForCausalLM
model = AutoAWQForCausalLM.from_quantized(model_path)
- Downloads last month
- 22
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.