Update README.md

README.md

@@ -3,12 +3,15 @@ license: apache-2.0
 ---
 # NEO
 
+[🤗Neo-Models](https://huggingface.co/collections/m-a-p/neo-models-66395a5c9662bb58d5d70f04) | [🤗Neo-Datasets](https://huggingface.co/collections/m-a-p/neo-models-66395a5c9662bb58d5d70f04) | [Github](https://github.com/multimodal-art-projection/MAP-NEO)
+
 Neo is a completely open source large language model, including code, all model weights, datasets used for training, and training details.
 
 ## Model
 
 | Model | Describe | Download | 
 |---|---|---|
+neo_7b| This repository contains the base model of neo_7b  | • [🤗 Hugging Face](https://huggingface.co/m-a-p/neo_7b)
 neo_7b_intermediate| This repo contains normal pre-training intermediate ckpts. A total of 3.7T tokens were learned at this phase. | • [🤗 Hugging Face](https://huggingface.co/m-a-p/neo_7b_intermediate)
 neo_7b_decay| This repo contains intermediate ckpts during the decay phase. A total of 720B tokens were learned at this phase.  | • [🤗 Hugging Face](https://huggingface.co/m-a-p/neo_7b_decay)
 neo_scalinglaw_980M | This repo contains ckpts related to scalinglaw experiments | • [🤗 Hugging Face](https://huggingface.co/m-a-p/neo_scalinglaw_980M)
@@ -21,7 +24,7 @@ neo_2b_general | This repo contains ckpts of 2b model trained using common domai
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-model_path = '<your-hf-model-path>'
+model_path = '<your-hf-model-path-with-tokenizer>'
 
 tokenizer = AutoTokenizer.from_pretrained(model_path, use_fast=False, trust_remote_code=True)