[max-examples] GUI: Improvements and fixes

- Bert: display top 5 examples by default
- Llamma3: use 3.1 models by default
- Rag: put example data in `ragdata` folder so it doesn't crash
- Stable Diffusion: fix data type being incorrect
- Yolo: move yoloconstants.py CLASS_NAMES into yolo.py

MODULAR_ORIG_COMMIT_REV_ID: 5567ef1680b1f697f5b1cacbcd897f1d08564301

examples/gui/pages/bert.py

@@ -92,6 +92,7 @@ def softmax(logits):
 model_state = st.empty()
 
 mlm = st.sidebar.checkbox("Masked Language Model", True)
+show_predictions = st.sidebar.checkbox("Show top 5 predictions", True)
 filename = "bert.torchscript"
 if mlm:
     filename = "bert-mlm.torchscript"
@@ -102,7 +103,6 @@ def softmax(logits):
 batch = st.sidebar.number_input("Batch Size", 1, 64)
 seq_len = st.sidebar.slider("Sequence Length", 128, 1024)
 input_text = st.text_input("Text Input", "Don't [MASK] about it")
-show_predictions = st.sidebar.checkbox("Show top 5 predictions")
 
 compile_torchscript(batch, seq_len, mlm)
 

examples/gui/pages/llama3.py

@@ -92,11 +92,11 @@ def start_llama3(
 )
 
 if quantization == "q4_0":
-    model_url = "https://huggingface.co/QuantFactory/Meta-Llama-3-8B-Instruct-GGUF/resolve/main/Meta-Llama-3-8B-Instruct.Q4_0.gguf"
+    model_url = "https://huggingface.co/QuantFactory/Meta-Llama-3-8B-Instruct-GGUF/resolve/main/Meta-Llama-3.1-8B-Instruct.Q4_0.gguf"
 elif quantization == "q4_k":
-    model_url = "https://huggingface.co/bartowski/Meta-Llama-3-8B-Instruct-GGUF/resolve/main/Meta-Llama-3-8B-Instruct-Q4_K_M.gguf"
+    model_url = "https://huggingface.co/bartowski/Meta-Llama-3-8B-Instruct-GGUF/resolve/main/Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf"
 elif quantization == "q6_k":
-    model_url = "https://huggingface.co/bartowski/Meta-Llama-3-8B-Instruct-GGUF/resolve/main/Meta-Llama-3-8B-Instruct-Q6_K.gguf"
+    model_url = "https://huggingface.co/bartowski/Meta-Llama-3-8B-Instruct-GGUF/resolve/main/Meta-Llama-3.1-8B-Instruct-Q6_K.gguf"
 
 model_url = st.sidebar.text_input("Model URL", value=model_url)
 os.makedirs(modular_cache_dir(), exist_ok=True)

examples/gui/pages/rag.py

@@ -10,16 +10,15 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ===----------------------------------------------------------------------=== #
-from pathlib import Path
 import os
 import subprocess
+from pathlib import Path
 
+import chromadb
 import openai
 import streamlit as st
-import chromadb
 from fastembed import TextEmbedding
 from llama_index.core import SimpleDirectoryReader
-
 from shared import download_file, kill_process, menu, modular_cache_dir
 
 st.set_page_config("RAG with Llama3", page_icon="🗣️ 📄")
@@ -153,11 +152,11 @@ def start_llama3(
 )
 
 if quantization == "q4_0":
-    model_url = "https://huggingface.co/QuantFactory/Meta-Llama-3-8B-GGUF/resolve/main/Meta-Llama-3-8B.Q4_0.gguf"
+    model_url = "https://huggingface.co/QuantFactory/Meta-Llama-3-8B-Instruct-GGUF/resolve/main/Meta-Llama-3.1-8B-Instruct.Q4_0.gguf"
 elif quantization == "q4_k":
-    model_url = "https://huggingface.co/bartowski/Meta-Llama-3-8B-Instruct-GGUF/resolve/main/Meta-Llama-3-8B-Instruct-Q4_K_M.gguf"
+    model_url = "https://huggingface.co/bartowski/Meta-Llama-3-8B-Instruct-GGUF/resolve/main/Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf"
 elif quantization == "q6_k":
-    model_url = "https://huggingface.co/bartowski/Meta-Llama-3-8B-Instruct-GGUF/resolve/main/Meta-Llama-3-8B-Instruct-Q6_K.gguf"
+    model_url = "https://huggingface.co/bartowski/Meta-Llama-3-8B-Instruct-GGUF/resolve/main/Meta-Llama-3.1-8B-Instruct-Q6_K.gguf"
 
 model_url = st.sidebar.text_input("Model URL", value=model_url)
 os.makedirs(modular_cache_dir(), exist_ok=True)

examples/gui/pages/stable-diffusion.py

@@ -120,7 +120,9 @@ def load_tokenizer(path):
             padding="max_length",
             max_length=tokenizer.model_max_length,
         )
-        input_ids = np.stack((prompt_p.input_ids, prompt_n.input_ids))
+        input_ids = np.stack((prompt_p.input_ids, prompt_n.input_ids)).astype(
+            np.int32
+        )
         encoder_hidden_states = txt_encoder.execute(input_ids=input_ids)[
             "last_hidden_state"
         ]

examples/gui/pages/yolo.py

@@ -127,6 +127,89 @@
 ONNX, then compiles it with MAX for faster inference!
 """
 
+CLASS_NAMES = [
+    "person",
+    "bicycle",
+    "car",
+    "motorcycle",
+    "airplane",
+    "bus",
+    "train",
+    "truck",
+    "boat",
+    "traffic light",
+    "fire hydrant",
+    "stop sign",
+    "parking meter",
+    "bench",
+    "bird",
+    "cat",
+    "dog",
+    "horse",
+    "sheep",
+    "cow",
+    "elephant",
+    "bear",
+    "zebra",
+    "giraffe",
+    "backpack",
+    "umbrella",
+    "handbag",
+    "tie",
+    "suitcase",
+    "frisbee",
+    "skis",
+    "snowboard",
+    "sports ball",
+    "kite",
+    "baseball bat",
+    "baseball glove",
+    "skateboard",
+    "surfboard",
+    "tennis racket",
+    "bottle",
+    "wine glass",
+    "cup",
+    "fork",
+    "knife",
+    "spoon",
+    "bowl",
+    "banana",
+    "apple",
+    "sandwich",
+    "orange",
+    "broccoli",
+    "carrot",
+    "hot dog",
+    "pizza",
+    "donut",
+    "cake",
+    "chair",
+    "couch",
+    "potted plant",
+    "bed",
+    "dining table",
+    "toilet",
+    "tv",
+    "laptop",
+    "mouse",
+    "remote",
+    "keyboard",
+    "cell phone",
+    "microwave",
+    "oven",
+    "toaster",
+    "sink",
+    "refrigerator",
+    "book",
+    "clock",
+    "vase",
+    "scissors",
+    "teddy bear",
+    "hair drier",
+    "toothbrush",
+]
+
 
 @st.cache_data(show_spinner="Downloading YOLO and exporting to ONNX")
 def download_and_export_yolo(model_path, height, width):

examples/gui/ragdata/mojo_functions.txt

@@ -0,0 +1,28 @@
+# Mojo Functions
+
+Mojo functions can be declared with either fn or def.
+
+The fn declaration enforces type-checking and memory-safe behaviors (Rust style), while def allows no type declarations and dynamic behaviors (Python style).
+
+For example, this def function doesn't require declaration of argument types or the return type:
+
+```mojo
+def greet(name):
+    return "Hello, " + name + "!"
+```
+
+While the same thing as an fn function requires that you specify the argument type and the return type like this:
+
+```mojo
+fn greet2(name: String) -> String:
+    return "Hello, " + name + "!"
+```
+
+Both functions have the same result, but the fn function provides compile-time checks to ensure the function receives and returns the correct types. Whereas, the def function might fail at runtime if it receives the wrong type.
+
+Currently, Mojo doesn't support top-level code in a .mojo (or .🔥) file, so every program must include a function named main() as the entry point. You can declare it with either def or fn:
+
+```mojo
+def main():
+   print("Hello, world!")
+```