7B AWQ
Collection
These models are selected for their compatibility with small 12GB memory GPUs. • 203 items • Updated • 2
Text Generation
Transformers
Safetensors
mistral
Merge
mergekit
lazymergekit
macadeliccc/WestLake-7B-v2-laser-truthy-dpo
FelixChao/WestSeverus-7B-DPO-v2
FelixChao/Faraday-7B
text-generation-inference
4-bit precision
awq
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("solidrust/Darcy-7b-AWQ")
model = AutoModelForCausalLM.from_pretrained("solidrust/Darcy-7b-AWQ")Quick Links
Darcy-7b - AWQ
Model description
Darcy-7b is a merge of the following models using LazyMergekit.
About AWQ
AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. Compared to GPTQ, it offers faster Transformers-based inference with equivalent or better quality compared to the most commonly used GPTQ settings.
AWQ models are currently supported on Linux and Windows, with NVidia GPUs only. macOS users: please use GGUF models instead.
It is supported by:
- Text Generation Webui - using Loader: AutoAWQ
- vLLM - version 0.2.2 or later for support for all model types.
- Hugging Face Text Generation Inference (TGI)
- Transformers version 4.35.0 and later, from any code or client that supports Transformers
- AutoAWQ - for use from Python code
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="solidrust/Darcy-7b-AWQ")