quicksearch-models-component

Dockerfile

@@ -37,7 +37,7 @@ RUN pyenv install ${PYTHON_VERSION} && \
     pyenv global ${PYTHON_VERSION} && \
     pyenv rehash && \
     pip install --no-cache-dir -U pip setuptools wheel && \
-    pip install "huggingface-hub" "hf-transfer" "gradio>=4.26.0"
+    pip install "huggingface-hub" "hf-transfer" "gradio>=4.26.0" "gradio_huggingfacehub_search==0.0.6"
 
 COPY --chown=1000 . ${HOME}/app
 RUN git clone https://github.com/ggerganov/llama.cpp

app.py

@@ -9,6 +9,8 @@ from huggingface_hub import snapshot_download
 from huggingface_hub import whoami
 from huggingface_hub import ModelCard
 
+from gradio_huggingfacehub_search import HuggingfaceHubSearch
+
 from textwrap import dedent
 
 LLAMA_LIKE_ARCHS = ["MistralForCausalLM", "LlamaForCausalLM"]
@@ -141,10 +143,10 @@ def process_model(model_id, q_method, hf_token, private_repo):
 iface = gr.Interface(
     fn=process_model,
     inputs=[
-        gr.Textbox(
-            lines=1,
+        HuggingfaceHubSearch(
             label="Hub Model ID",
-            info="Repo/model",
+            placeholder="Search for model id on Huggingface",
+            search_type="model",
         ),
         gr.Dropdown(
             ["Q2_K", "Q3_K_S", "Q3_K_M", "Q3_K_L", "Q4_0", "Q4_K_S", "Q4_K_M", "Q5_0", "Q5_K_S", "Q5_K_M", "Q6_K", "Q8_0"],
@@ -175,4 +177,4 @@ iface = gr.Interface(
 )
 
 # Launch the interface
-iface.queue(default_concurrency_limit=1, max_size=5).launch(debug=True)
+iface.queue(default_concurrency_limit=1, max_size=5).launch(debug=True)