update

app.py

@@ -13,17 +13,15 @@ We present ***TIGERScore***, a **T**rained metric that follows **I**nstruction *
 
 """
 
-EXAMPLES_DATASET = load_dataset("TIGER-Lab/MetricInstruct", split="train")
+EXAMPLES_DATASET = load_dataset("TIGER-Lab/MetricInstruct", split="train", streaming=True)
 SHUFFLED_EXAMPLES_DATASET = EXAMPLES_DATASET.shuffle(seed=42)
 EXAMPLES = []
 fields = ["instruction", "input_context", "hypo_output"]
 print("Loading examples...")
-for i, ex in enumerate(SHUFFLED_EXAMPLES_DATASET):
-    if any([not ex[field] for field in fields]):
-        continue
+for i, ex in enumerate(SHUFFLED_EXAMPLES_DATASET.take(100)):
+    # if any([not ex[field] for field in fields]):
+    #     continue
     EXAMPLES.append([ex[field] for field in fields])
-    if i >= 100:
-        break
 
 scorer = TIGERScorer("TIGER-Lab/TIGERScore-7B-GGUF", use_llamacpp=True)
 
@@ -35,15 +33,15 @@ def submit_fn(input_context, generation_instruction, hypo_output, max_new_tokens
         max_new_tokens=max_new_tokens,
         temperature=temperature,
         top_p=top_p,
-    )[0]['raw_output'].strip()   
+    )[0]['raw_output'].strip() 
         
         
 
-def get_examples(task, inst_textbox, input_textbox, hypo_output_textbox):
-    return gr.Dropdown.update(value=task), inst_textbox, input_textbox, hypo_output_textbox
+def get_examples(inst_textbox, input_textbox, hypo_output_textbox):
+    return inst_textbox, input_textbox, hypo_output_textbox
 
-def clear_all(task, inst_textbox, input_textbox, hypo_output_textbox):
-    return gr.Dropdown.update(value=task), "", "", ""
+def clear_all(inst_textbox, input_textbox, hypo_output_textbox):
+    return "", "", ""
 
 with gr.Blocks(theme='gradio/soft') as demo:
      

requirements.txt

@@ -1,3 +1,2 @@
 git+https://github.com/TIGER-AI-Lab/TIGERScore.git
-transformers==4.33.2
 datasets==2.14.5