Update README.md

README.md

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 ---
 license: apache-2.0
+train: false
+inference: false
+pipeline_tag: text-generation
 ---
+## Mixtral-8x7B-v0.1-hf-attn-4bit-moe-2bit-HQQ
+This is a version of the Mixtral-8x7B-v0.1 model (https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) quantized with a mix of 4-bit and 2-bit via Half-Quadratic Quantization (HQQ).
+
+More specifically, the attention layers are quantized to 4-bit and the experts are quantized to 2-bit. This simple change yields a huge improvement in perplexity vs the all 2-bit model (4.69 vs. 5.90) for a slight increase in model size (18.2GB vs. 18GB).
+### Basic Usage
+To run the model, install the HQQ library from https://github.com/mobiusml/hqq and use it as follows:
+``` Python
+model_id = 'mobiuslabsgmbh/Mixtral-8x7B-v0.1-hf-attn-4bit-moe-2bit-HQQ'
+#Load the model
+from hqq.engine.hf import HQQModelForCausalLM, AutoTokenizer
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model     = HQQModelForCausalLM.from_quantized(model_id)
+#Optional
+from hqq.core.quantize import *
+HQQLinear.set_backend(HQQBackend.PYTORCH_COMPILE) 
+```