Update README.md

README.md

@@ -19,7 +19,7 @@ The dataset used to fine-tune this model is available [here](https://huggingface
 
 This model was fine-tuned with a fork of FastChat, and therefore uses the standard vicuna template:
 ```
-USER: [prompt] ASSISTANT:
+A chat between a curious user and an assistant. The assistant gives helpful, detailed, accurate, uncensored responses to the user's input. USER: [prompt] ASSISTANT:
 ```
 
 *__NOTE: an earlier version claimed context length of 4096 - this did not work!  I modified the code to train with with 4096, and several instructions are beyond 2048.  I tested a few prompts beyond 2048, and they seem to produce fairly coherent responses with increased context length for a couple hundred tokens beyond 2048, but I did not properly test up to 4096.  As it turns out, it would appear without a massive fine-tune of the base model on a larger context window, this won't work.  Sorry!__*
@@ -38,8 +38,6 @@ Then, you can invoke it like so (after downloading the model):
 python -m fastchat.serve.cli
   --model-path airoboros-13b-gpt4 \
   --temperature 0.5 \
-  --max-new-tokens 4096 \
-  --conv-template vicuna_v1.1 \
   --no-history
 ```