feat: mistral_7b_ielts_evaluator

app.py

@@ -2,10 +2,12 @@ from typing import *
 import gradio as gr
 from model.IELTS_essay_scoring import grade_IELTS_essay_scoring
 from model.Engessay_grading_ML import grade_Engessay_grading_ML
+from model.mistral_7b_ielts_evaluator import grade_mistral_7b_ielts_evaluator
 
 models = {
     "IELTS_essay_scoring": grade_IELTS_essay_scoring,
     "Engessay_grading_ML": grade_Engessay_grading_ML,
+    "mistral_7b_ielts_evaluator": grade_mistral_7b_ielts_evaluator,
 }
 
 

model/mistral_7b_ielts_evaluator.py

@@ -0,0 +1,32 @@
+from typing import *
+import torch
+import numpy as np
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+import spaces
+
+model_name = "chillies/mistral-7b-ielts-evaluator-q4"
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+
+@spaces.GPU()
+@torch.no_grad()
+def grade_mistral_7b_ielts_evaluator(question: str, answer: str) -> Tuple[float, str]:
+    text = f"{question} {answer}"
+
+    inputs = tokenizer(
+        text,
+        return_tensors="pt",
+        padding=True,
+        truncation=True,
+    )
+
+    outputs = model(**inputs)
+    score = outputs.logits.argmax(dim=-1).item()
+    print(score)
+
+    overall_score = float(score)
+
+    comment = ""
+
+    return overall_score, comment