revert naming paths

README.md

@@ -11,18 +11,18 @@ datasets:
   - tatsu-lab/alpaca
 ---
 
-# StableVicuna-13B: Fine-Tuned with RLHF
+# StableVicuna-13B
 
 ## Model Description
 
-StableVicuna-13B is a [Vicuna-13B](https://vicuna.lmsys.org/) model fine-tuned using reinforcement learning from human feedback (RLHF) via Proximal Policy Optimization (PPO) on various conversational and instructional datasets.
+StableVicuna-13B is a [Vicuna-13B v1.0](https://vicuna.lmsys.org/) model fine-tuned using reinforcement learning from human feedback (RLHF) via Proximal Policy Optimization (PPO) on various conversational and instructional datasets.
 
 ### Apply Delta Weights
 
-StableVicuna-13B cannot be used from the `stability/stable-vicuna-13b-delta` weights alone. To obtain the correct model, one must add back the difference between LLaMA 13B and `stability/stable-vicuna-13b-delta` weights. We provide the [`apply_delta.py`](https://huggingface.co/CarperAI/stable-vicuna-13b-delta/raw/main/apply_delta.py) script to automate the conversion, which you can run as:
+StableVicuna-13B cannot be used from the `CarperAI/stable-vicuna-13b-delta` weights alone. To obtain the correct model, one must add back the difference between LLaMA 13B and `CarperAI/stable-vicuna-13b-delta` weights. We provide the [`apply_delta.py`](https://huggingface.co/CarperAI/stable-vicuna-13b-delta/raw/main/apply_delta.py) script to automate the conversion, which you can run as:
 
 ```sh
-python3 apply_delta.py --base /path/to/model_weights/llama-13b --target stable-vicuna-13b --delta stabilityai/stable-vicuna-13b-delta
+python3 apply_delta.py --base /path/to/model_weights/llama-13b --target stable-vicuna-13b --delta CarperAI/stable-vicuna-13b-delta
 ```
 
 
@@ -81,7 +81,7 @@ The reward model used during RLHF was also trained on [OpenAssistant Conversatio
 
 ### Training Procedure
 
-`stabilityai/sstable-vicuna-13b-delta` was trained using PPO as implemented in [`trlX`](https://github.com/CarperAI/trlx/blob/main/trlx/trainer/accelerate_ppo_trainer.py) with the following configuration:
+`CarperAI/sstable-vicuna-13b-delta` was trained using PPO as implemented in [`trlX`](https://github.com/CarperAI/trlx/blob/main/trlx/trainer/accelerate_ppo_trainer.py) with the following configuration:
 
 |  Hyperparameter   |  Value  |
 |-------------------|---------|
@@ -118,7 +118,7 @@ The base LLaMA model is trained on various data, some of which may contain offen
 
 ## Acknowledgements
 
-This work would not have been possible without the support of [CarperAI](https://carper.ai/).
+This work would not have been possible without the support of [Stability AI](https://stability.ai/).
 
 ## Citations