Upload folder using huggingface_hub

README.md

@@ -1,12 +1,6 @@
 ---
-title: Google Flan T5
-emoji: 🐠
-colorFrom: red
-colorTo: purple
-sdk: gradio
-sdk_version: 4.18.0
+title: google-flan-t5
 app_file: app.py
-pinned: false
+sdk: gradio
+sdk_version: 3.44.4
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,49 @@
+from langchain.prompts import PromptTemplate
+from langchain.llms import CTransformers
+import os
+import gradio as gr
+
+def GetLlamaResponse(topic):
+    llm = CTransformers(
+        model_type="google-flan",
+        model="tf_model.h5",
+        config={"max_new_tokens": 64, "temperature": 0.75},
+    )
+    template = """
+    You are a helpful assistant
+    """
+    prompt = PromptTemplate(
+        input_variables=["topic", "word_count", "temperature"],
+        template=template,
+    )
+
+    response = llm(
+        prompt.format(
+            word_count=64,
+            temperature=0.4,
+            topic=topic,
+        )
+    )
+
+    return response
+
+inputs_image_url = [
+    gr.Textbox(type="text", label="Topic Name"),
+]
+
+outputs_result_dict = [
+    gr.Textbox(type="text", label="Result"),
+]
+
+interface_image_url = gr.Interface(
+    fn=GetLlamaResponse,
+    inputs=inputs_image_url,
+    outputs=outputs_result_dict,
+    title="Text Generation",
+    cache_examples=False,
+)
+
+gr.TabbedInterface(
+    [interface_image_url],
+    tab_names=['Some inference']
+).queue().launch()

requirements.txt

@@ -0,0 +1,6 @@
+sentence-transformers
+uvicorn
+ctransformers
+langchain
+python-box
+gradio

tf_model.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1e41a6feb46b32caa15dde6cf644fce4fd96614f42a1e69d10b5a4069c89f4ce
+size 3396920920