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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+TrillaTag-0.0.3_V1.gguf filter=lfs diff=lfs merge=lfs -text

TrillaTag-0.0.3_V1.gguf

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+version https://git-lfs.github.com/spec/v1
+oid sha256:edfe79cdc4ecdce7338279a930fdc6ec3a5ce36c0aed475a9423570fb4b1e5e4
+size 7161089728

app.py

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+#!/usr/bin/env python
+# coding: utf-8
+
+# In[ ]:
+
+
+import gradio as gr
+from pydantic import BaseModel
+
+# Assuming ctransformers is a library that allows loading your model
+from ctransformers import AutoModelForCausalLM
+
+# Load your model (adjust the path to where your model is located)
+llm = AutoModelForCausalLM.from_pretrained("TrillaTag-0.0.3_V1.gguf",
+                                           model_type='mistral',
+                                           max_new_tokens=1096,
+                                           threads=3)
+
+# Define a function that will use your model to generate a response
+def generate_completion(prompt):
+    try:
+        # Generate a response from your model based on the user's prompt
+        response = llm.generate(prompt)
+        return response
+    except Exception as e:
+        # If something goes wrong, you could log the exception or handle it as needed
+        return str(e)  # For simplicity, we just return the error as a string
+
+# Create a Gradio interface
+# The first argument is the function to call (our generate_completion function),
+# followed by the inputs and outputs specifications
+iface = gr.Interface(fn=generate_completion,
+                     inputs=gr.inputs.Textbox(lines=2, placeholder="Enter your prompt here..."),
+                     outputs="text",
+                     title="TrillaTag Model Generator",
+                     description="Enter a prompt to generate text from the TrillaTag Model.")
+
+# Launch the Gradio app
+# Setting share=True generates a public link for the interface that anyone can access.
+# This is useful for sharing your model with others but should be used cautiously for public-facing applications.
+iface.launch(share=True)
+

requirements.txt

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+python-multipart
+fastapi
+pydantic
+uvicorn
+requests
+python-dotenv
+ctransformers
+absl-py                       
+accelerate                    
+aiohttp                       
+aiosignal                     
+alabaster                     
+anaconda-client               
+anaconda-navigator            
+anaconda-project              
+gradio