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app.py

@@ -38,12 +38,12 @@ def main():
             """
         )
     ## Default values for advanced settings
-    user_seed = 27 # Remove if we're not rigging the "random" demo
+    user_seed = None # Set to a value if we want to rig the "random" demo
     generation_method = "top-k"
     specified_k = 5
     specified_nucleus = 0.5
     specified_temperature = 0.9
-    max_tokens = 400
+    max_tokens = 500
 
     if st.checkbox("Show Advanced Settings"):
         user_seed = st.number_input("Randomness Seed:", value = None, step = 1, placeholder="Use to replicate response", min_value = 1)
@@ -58,11 +58,10 @@ def main():
         if generation_method == "temperature":
             specified_temperature = st.number_input("Value for temperature:", value = 0.9, step = 0.05, min_value = 0.0, max_value = 1.0)
 
-        max_tokens = st.slider('Max Tokens Generated:', 100, 500, 400)
+        max_tokens = st.slider('Max Tokens Generated:', 100, 800, 500)
 
 
 
-    st.markdown(f'random seed: {user_seed}')
 
 
     # model_version = st.radio("Which model would you like to use?", ["smoll", "beeg"])

better_transformer.py

@@ -282,7 +282,7 @@ def set_seed(seed = 42):
     np.random.seed(seed)
     os.environ['PYTHONHASHSEED'] = str(seed)
     torch.manual_seed(seed)
-    torch.cuda.manual_seed(seed)
+    #torch.cuda.manual_seed(seed)
     # torch.cuda.manual_seed_all(seed) # if multi-GPU
     torch.backends.cudnn.deterministic=True # only applies to CUDA convolution operations
     torch.backends.cudnn.benchmark = False
@@ -359,7 +359,6 @@ def generate(model, tokenizer, device, method=None, k=None,
     if deterministic is not None:
         set_seed(deterministic)
 
-    st.markdown(f"Deterministic: {deterministic}")
 
     if cond != "":