From 498cfe65488d183ef4dde7a1675a7cc37ef8ded8 Mon Sep 17 00:00:00 2001
From: Charles Frye <charles@modal.com>
Date: Sun, 17 Nov 2024 21:11:37 -0800
Subject: [PATCH] removes instructor embeddings example

---
 06_gpu_and_ml/embeddings/instructor.py | 73 --------------------------
 1 file changed, 73 deletions(-)
 delete mode 100644 06_gpu_and_ml/embeddings/instructor.py

diff --git a/06_gpu_and_ml/embeddings/instructor.py b/06_gpu_and_ml/embeddings/instructor.py
deleted file mode 100644
index 968cd3a96..000000000
--- a/06_gpu_and_ml/embeddings/instructor.py
+++ /dev/null
@@ -1,73 +0,0 @@
-# # Create Instructor Embeddings on Modal
-#
-# This example runs the [Instructor](https://github.com/xlang-ai/instructor-embedding) embedding model and runs a simple sentence similarity computation.
-
-import modal
-
-MODEL_DIR = "/model"
-
-
-image = (
-    modal.Image.debian_slim(python_version="3.10")
-    .apt_install("git")
-    .run_commands(
-        "git clone https://github.com/HKUNLP/instructor-embedding",
-        # Package doesn't define it's requirements properly?
-        "cd instructor-embedding && pip install -r requirements.txt",
-    )
-    .pip_install("InstructorEmbedding")
-)
-
-app = modal.App("instructor", image=image)
-
-with image.imports():
-    from InstructorEmbedding import INSTRUCTOR
-
-
-@app.cls(gpu="any")
-class InstructorModel:
-    @modal.build()
-    def download_model(self):
-        model = INSTRUCTOR("hkunlp/instructor-large")
-        model.save(MODEL_DIR)
-
-    @modal.enter()
-    def enter(self):
-        self.model = INSTRUCTOR(MODEL_DIR, device="cuda")
-
-    @modal.method()
-    def compare(self, sentences_a, sentences_b):
-        from sklearn.metrics.pairwise import cosine_similarity
-
-        embeddings_a = self.model.encode(sentences_a)
-        embeddings_b = self.model.encode(sentences_b)
-        similarities = cosine_similarity(embeddings_a, embeddings_b)
-        return similarities.tolist()
-
-
-@app.local_entrypoint()
-def run():
-    sentences_a = [
-        [
-            "Represent the Science sentence: ",
-            "Parton energy loss in QCD matter",
-        ],
-        [
-            "Represent the Financial statement: ",
-            "The Federal Reserve on Wednesday raised its benchmark interest rate.",
-        ],
-    ]
-    sentences_b = [
-        [
-            "Represent the Science sentence: ",
-            "The Chiral Phase Transition in Dissipative Dynamics",
-        ],
-        [
-            "Represent the Financial statement: ",
-            "The funds rose less than 0.5 per cent on Friday",
-        ],
-    ]
-
-    model = InstructorModel()
-    similarities = model.compare.remote(sentences_a, sentences_b)
-    print(similarities)