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README.md
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---
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license: apache-2.0
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base_model: BEE-spoke-data/beecoder-220M-python
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datasets:
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- BEE-spoke-data/pypi_clean-deduped
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- bigcode/the-stack-smol-xl
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- EleutherAI/proof-pile-2
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language:
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- en
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tags:
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- python
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- codegen
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- markdown
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- smol_llama
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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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inference:
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parameters:
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max_new_tokens: 64
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min_new_tokens: 8
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do_sample: true
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epsilon_cutoff: 0.0008
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temperature: 0.3
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top_p: 0.9
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repetition_penalty: 1.02
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no_repeat_ngram_size: 8
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renormalize_logits: true
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widget:
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- text: "def add_numbers(a, b):\n return\n"
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example_title: Add Numbers Function
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- text: "class Car:\n def __init__(self, make, model):\n self.make = make\n\
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\ self.model = model\n\n def display_car(self):\n"
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example_title: Car Class
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- text: 'import pandas as pd
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data = {''Name'': [''Tom'', ''Nick'', ''John''], ''Age'': [20, 21, 19]}
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df = pd.DataFrame(data).convert_dtypes()
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# eda
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'
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example_title: Pandas DataFrame
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- text: "def factorial(n):\n if n == 0:\n return 1\n else:\n"
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example_title: Factorial Function
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- text: "def fibonacci(n):\n if n <= 0:\n raise ValueError(\"Incorrect input\"\
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)\n elif n == 1:\n return 0\n elif n == 2:\n return 1\n \
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\ else:\n"
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example_title: Fibonacci Function
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- text: 'import matplotlib.pyplot as plt
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import numpy as np
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x = np.linspace(0, 10, 100)
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# simple plot
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'
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example_title: Matplotlib Plot
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- text: "def reverse_string(s:str) -> str:\n return\n"
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example_title: Reverse String Function
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- text: "def is_palindrome(word:str) -> bool:\n return\n"
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example_title: Palindrome Function
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- text: "def bubble_sort(lst: list):\n n = len(lst)\n for i in range(n):\n \
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\ for j in range(0, n-i-1):\n"
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example_title: Bubble Sort Function
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- text: "def binary_search(arr, low, high, x):\n if high >= low:\n mid =\
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\ (high + low) // 2\n if arr[mid] == x:\n return mid\n \
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\ elif arr[mid] > x:\n"
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example_title: Binary Search Function
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pipeline_tag: text-generation
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---
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# ysn-rfd/beecoder-220M-python-Q8_0-GGUF
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This model was converted to GGUF format from [`BEE-spoke-data/beecoder-220M-python`](https://huggingface.co/BEE-spoke-data/beecoder-220M-python) 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/BEE-spoke-data/beecoder-220M-python) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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```bash
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brew install 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 ysn-rfd/beecoder-220M-python-Q8_0-GGUF --hf-file beecoder-220m-python-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 ysn-rfd/beecoder-220M-python-Q8_0-GGUF --hf-file beecoder-220m-python-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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Step 1: Clone llama.cpp from GitHub.
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```
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git clone https://github.com/ggerganov/llama.cpp
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```
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Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
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```
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cd llama.cpp && LLAMA_CURL=1 make
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```
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Step 3: Run inference through the main binary.
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```
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./llama-cli --hf-repo ysn-rfd/beecoder-220M-python-Q8_0-GGUF --hf-file beecoder-220m-python-q8_0.gguf -p "The meaning to life and the universe is"
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```
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or
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```
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./llama-server --hf-repo ysn-rfd/beecoder-220M-python-Q8_0-GGUF --hf-file beecoder-220m-python-q8_0.gguf -c 2048
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```
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