t

app.py

@@ -2,8 +2,8 @@
 import gradio as gr
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-model = AutoModelForCausalLM.from_pretrained("EleutherAI/gpt-j-6B")
 tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-j-6B")
+model = AutoModelForCausalLM.from_pretrained("EleutherAI/gpt-j-6B")
 
 # prompt = "In a shocking finding, scientists discovered a herd of unicorns living in a remote, " \
 #          "previously unexplored valley, in the Andes Mountains. Even more surprising to the " \
@@ -15,7 +15,7 @@ def predict(text):
     gen_tokens = model.generate(input_ids, do_sample=True, temperature=0.9, max_length=100)
     gen_text = tokenizer.batch_decode(gen_tokens)[0]
     return gen_text
-    
+
 iface = gr.Interface(fn=predict, inputs="text", outputs="text")
 iface.launch()
 

requirements.txt

@@ -1,7 +1,4 @@
-tensorflow==2.7.0
-tensorflow-estimator==2.7.0
-tensorflow-io-gcs-filesystem==0.23.1
-transformers @ git+https://github.com/StellaAthena/transformers@f1b4c9f69cebfee59833cde9e5c6692b87c63eff
-flax==0.3.6
-torch==1.10.1
-
+transformers
+flax
+torch
+tensorflow