Update README.md

README.md

@@ -21,9 +21,9 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 
 tokenizer = AutoTokenizer.from_pretrained("StabilityAI/stablelm-base-alpha-7b")
 model = AutoModelForCausalLM.from_pretrained("StabilityAI/stablelm-base-alpha-7b")
-model.half().cuda()
+model.half()
 
-inputs = tokenizer("What's your mood today?", return_tensors="pt").to('cuda')
+inputs = tokenizer("What's your mood today?", return_tensors="pt")
 tokens = model.generate(
   **inputs,
   max_new_tokens=64,
@@ -55,7 +55,7 @@ print(tokenizer.decode(tokens[0], skip_special_tokens=True))
 
 ### Training Procedure
 
-Models are pre-trained on the aforementioned dataset in mixed-precision (FP16) and optimized with Adam. We outline the complete hyperparameters choices in the project's GitHub repository **{TODO: FILL IN LINK}**.
+Models are pre-trained on the aforementioned dataset in mixed-precision (FP16), optimized with Adam, and trained using the NeoX tokenizer with a vocabulary size of 50,257. We outline the complete hyperparameters choices in the project's GitHub repository **{TODO: FILL IN LINK}**.
 
 ## Use and Limitations