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ghosthets commited on 6 days ago

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be5cf1f

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1 Parent(s): 45d6ddf

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index.html +57 -22

index.html CHANGED Viewed

@@ -3,8 +3,8 @@
     <head>
         <meta charset="utf-8">
         <meta name="viewport" content="width=device-width, initial-scale=1">
-        <title>Gradio-Lite: Serverless Gradio Running Entirely in Your Browser</title>
-        <meta name="description" content="Gradio-Lite: Serverless Gradio Running Entirely in Your Browser">
         <script type="module" crossorigin src="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.js"></script>
         <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.css" />
@@ -21,36 +21,71 @@
         <gradio-lite>
             <gradio-file name="app.py" entrypoint>
 import gradio as gr
-from filters import as_gray
-def process(input_image):
-    output_image = as_gray(input_image)
-    return output_image
-demo = gr.Interface(
-    process,
-    "image",
-    "image",
-    examples=["lion.jpg", "logo.png"],
-)
-demo.launch()
-            </gradio-file>
-            <gradio-file name="filters.py">
-from skimage.color import rgb2gray
-def as_gray(image):
-    return rgb2gray(image)
             </gradio-file>
-            <gradio-file name="lion.jpg" url="https://raw.githubusercontent.com/gradio-app/gradio/main/gradio/test_data/lion.jpg" />
-            <gradio-file name="logo.png" url="https://raw.githubusercontent.com/gradio-app/gradio/main/guides/assets/logo.png" />
             <gradio-requirements>
-# Same syntax as requirements.txt
-scikit-image
             </gradio-requirements>
         </gradio-lite>
     </body>

     <head>
         <meta charset="utf-8">
         <meta name="viewport" content="width=device-width, initial-scale=1">
+        <title>ClokCEM - Customer Executive Model</title>
+        <meta name="description" content="354M parameter model for enterprise customer support">
         <script type="module" crossorigin src="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.js"></script>
         <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.css" />
         <gradio-lite>
             <gradio-file name="app.py" entrypoint>
 import gradio as gr
+import torch
+from huggingface_hub import hf_hub_download
+from safetensors.torch import load_file
+MODEL_REPO = "clokai/CLOK-CEM"
+print("Loading model...")
+from configuration_clokcem import ClokcemConfig
+from modeling_clokcem import ClokcemForCausalLM
+from transformers import AutoTokenizer
+config = ClokcemConfig()
+model = ClokcemForCausalLM(config)
+weights_path = hf_hub_download(repo_id=MODEL_REPO, filename="model.safetensors")
+sd = load_file(weights_path)
+model.load_state_dict(sd, strict=False)
+model.eval()
+tokenizer = AutoTokenizer.from_pretrained(MODEL_REPO)
+print("Model ready!")
+def chat(message, history, temperature, max_tokens):
+    device = next(model.parameters()).device
+    formatted = f"<|system|>You are a helpful customer care assistant.<|user|>{message}<|assistant|>"
+    inputs = tokenizer(formatted, return_tensors="pt").to(device)
+    generated = []
+    input_ids = inputs["input_ids"]
+    for _ in range(max_tokens):
+        with torch.no_grad():
+            logits = model(input_ids).logits
+        probs = torch.softmax(logits[:, -1, :] / temperature, dim=-1)
+        next_token = torch.multinomial(probs, num_samples=1)
+        if next_token.item() == tokenizer.eos_token_id:
+            break
+        generated.append(next_token.item())
+        input_ids = torch.cat([input_ids, next_token], dim=-1)
+    return tokenizer.decode(generated, skip_special_tokens=True)
+demo = gr.ChatInterface(
+    fn=chat,
+    title="ClokCEM - Customer Executive Model",
+    description="354M parameter model for enterprise customer support",
+    additional_inputs=[
+        gr.Slider(0.1, 2.0, value=0.6, step=0.1, label="Temperature"),
+        gr.Slider(50, 500, value=200, step=50, label="Max Tokens"),
+    ],
+)
+demo.launch()
             </gradio-file>
+            <gradio-file name="configuration_clokcem.py" url="https://huggingface.co/clokai/CLOK-CEM/resolve/main/configuration_clokcem.py" />
+            <gradio-file name="modeling_clokcem.py" url="https://huggingface.co/clokai/CLOK-CEM/resolve/main/modeling_clokcem.py" />
             <gradio-requirements>
+torch
+transformers
+safetensors
+huggingface_hub
+gradio
             </gradio-requirements>
         </gradio-lite>
     </body>