Upload folder using huggingface_hub

.gitattributes

@@ -34,3 +34,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 tokenizer.json filter=lfs diff=lfs merge=lfs -text
+figures/new_logo.png filter=lfs diff=lfs merge=lfs -text
+figures/performance.png filter=lfs diff=lfs merge=lfs -text
+figures/wechat.png filter=lfs diff=lfs merge=lfs -text

README.md

@@ -66,11 +66,11 @@ The highlights from `dots.llm1` include:
 
 ## 3. dots.llm1.inst.FP8-dynamic 
 
-### Docker (vllm)
-
 We release the quantized `dots.llm1.inst.FP8-dynamic` model, which retains approximately 98% of the original performance after quantization. 
 
-run vllm inference using docker `rednote-hilab/vllm-openai-v0.9.1`. The docker images are available on [Docker Hub](https://hub.docker.com/repository/docker/rednotehilab/dots1/tags), based on the official images.
+### Docker (vllm)
+
+For convenience, we recommend running vLLM inference using our Docker image `rednote-hilab/vllm-openai-v0.9.1`, , which is available on [Docker Hub](https://hub.docker.com/repository/docker/rednotehilab/dots1/tags).
 
 ```bash
 python3 -m vllm.entrypoints.openai.api_server --model rednote-hilab/dots.llm1.inst.FP8-dynamic --tensor-parallel-size 4 --pipeline-parallel-size 1 --trust-remote-code --served-model-name dots1