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+ ---
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+ language:
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+ - en
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+ license: apache-2.0
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+ library_name: transformers
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+ tags:
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+ - python
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+ - java
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+ - cpp
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+ - sql
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+ - function calling
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+ - unit tests
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+ - causalLM
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+ - codeLLAMA modified archi
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+ - document
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+ - code
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+ - code2doc
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+ - instruction_tuned
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+ - basemodel
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+ - pytorch
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+ - docstring
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+ - documentation
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+ - text-generation-inference
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+ - llama-cpp
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+ - gguf-my-repo
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+ metrics:
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+ - accuracy
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+ pipeline_tag: text-generation
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+ widget:
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+ - text: '<example_response>--code:def function_divide2(x): return x / 2--question:Document
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+ the code--doc:Description:This function takes a number and divides it by 2.Parameters:-
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+ x (numeric): The input value to be divided by 2.Returns:- float: The result of
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+ x divided by 2.Example:To call the function, use the following code:function_divide2(1.0)</example_response><function_code>def
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+ _plot_bounding_polygon(polygons_coordinates, output_html_path=bounding_polygon_map.html):map_center
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+ = [sum([coord[0]for polygon_coords in polygons_coordinatesfor coord in polygon_coords])/
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+ sum([len(polygon_coords) for polygon_coords in polygons_coordinates]),sum([coord[1]for
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+ polygon_coords in polygons_coordinatesfor coord in polygon_coords])/ sum([len(polygon_coords)
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+ for polygon_coords in polygons_coordinates]),]my_map = folium.Map(location=map_center,
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+ zoom_start=12)for polygon_coords in polygons_coordinates:folium.Polygon(locations=polygon_coords,color=blue,fill=True,fill_color=blue,fill_opacity=0.2,).add_to(my_map)marker_cluster
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+ = MarkerCluster().add_to(my_map)for polygon_coords in polygons_coordinates:for
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+ coord in polygon_coords:folium.Marker(location=[coord[0], coord[1]], popup=fCoordinates:
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+ {coord}).add_to(marker_cluster)draw = Draw(export=True)draw.add_to(my_map)my_map.save(output_html_path)return
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+ output_html_path</function_code><question>Document the python code above giving
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+ function description ,parameters and return type and example how to call the function</question><doc>'
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+ example_title: example
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+ ---
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+
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+ # NikolayKozloff/pip-library-etl-1.3b-Q8_0-GGUF
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+ This model was converted to GGUF format from [`PipableAI/pip-library-etl-1.3b`](https://huggingface.co/PipableAI/pip-library-etl-1.3b) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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+ Refer to the [original model card](https://huggingface.co/PipableAI/pip-library-etl-1.3b) for more details on the model.
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+ ## Use with llama.cpp
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+
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+ Install llama.cpp through brew.
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+
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+ ```bash
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+ brew install ggerganov/ggerganov/llama.cpp
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+ ```
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+ Invoke the llama.cpp server or the CLI.
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+
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+ CLI:
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+
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+ ```bash
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+ llama-cli --hf-repo NikolayKozloff/pip-library-etl-1.3b-Q8_0-GGUF --model pip-library-etl-1.3b.Q8_0.gguf -p "The meaning to life and the universe is"
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+ ```
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+
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+ Server:
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+
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+ ```bash
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+ llama-server --hf-repo NikolayKozloff/pip-library-etl-1.3b-Q8_0-GGUF --model pip-library-etl-1.3b.Q8_0.gguf -c 2048
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+ ```
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+
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+ Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
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+
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+ ```
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+ git clone https://github.com/ggerganov/llama.cpp && cd llama.cpp && make && ./main -m pip-library-etl-1.3b.Q8_0.gguf -n 128
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+ ```