Text Generation
Transformers
GGUF
PyTorch
English
python
java
cpp
sql
function calling
unit tests
causalLM
codeLLAMA modified archi
document
code
code2doc
instruction_tuned
basemodel
docstring
documentation
text-generation-inference
plan
planner
llama-cpp
gguf-my-repo
Inference Endpoints
conversational
NikolayKozloff
commited on
Commit
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Parent(s):
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Upload README.md with huggingface_hub
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README.md
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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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- plan
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- planner
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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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# NikolayKozloff/pip-code-bandit-Q8_0-GGUF
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This model was converted to GGUF format from [`PipableAI/pip-code-bandit`](https://huggingface.co/PipableAI/pip-code-bandit) 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-code-bandit) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew.
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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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CLI:
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```bash
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llama-cli --hf-repo NikolayKozloff/pip-code-bandit-Q8_0-GGUF --model pip-code-bandit.Q8_0.gguf -p "The meaning to life and the universe is"
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```
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Server:
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```bash
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llama-server --hf-repo NikolayKozloff/pip-code-bandit-Q8_0-GGUF --model pip-code-bandit.Q8_0.gguf -c 2048
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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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git clone https://github.com/ggerganov/llama.cpp && cd llama.cpp && make && ./main -m pip-code-bandit.Q8_0.gguf -n 128
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```
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