--- base_model: BEE-spoke-data/beecoder-220M-python datasets: - BEE-spoke-data/pypi_clean-deduped - bigcode/the-stack-smol-xl - EleutherAI/proof-pile-2 inference: false language: - en license: apache-2.0 metrics: - accuracy model_creator: BEE-spoke-data model_name: beecoder-220M-python pipeline_tag: text-generation quantized_by: afrideva tags: - python - codegen - markdown - smol_llama - gguf - ggml - quantized - q2_k - q3_k_m - q4_k_m - q5_k_m - q6_k - q8_0 widget: - example_title: Add Numbers Function text: "def add_numbers(a, b):\n return\n" - example_title: Car Class text: "class Car:\n def __init__(self, make, model):\n self.make = make\n \ self.model = model\n\n def display_car(self):\n" - example_title: Pandas DataFrame text: 'import pandas as pd data = {''Name'': [''Tom'', ''Nick'', ''John''], ''Age'': [20, 21, 19]} df = pd.DataFrame(data).convert_dtypes() # eda ' - example_title: Factorial Function text: "def factorial(n):\n if n == 0:\n return 1\n else:\n" - example_title: Fibonacci Function text: "def fibonacci(n):\n if n <= 0:\n raise ValueError(\"Incorrect input\")\n \ elif n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n" - example_title: Matplotlib Plot text: 'import matplotlib.pyplot as plt import numpy as np x = np.linspace(0, 10, 100) # simple plot ' - example_title: Reverse String Function text: "def reverse_string(s:str) -> str:\n return\n" - example_title: Palindrome Function text: "def is_palindrome(word:str) -> bool:\n return\n" - example_title: Bubble Sort Function text: "def bubble_sort(lst: list):\n n = len(lst)\n for i in range(n):\n for j in range(0, n-i-1):\n" - example_title: Binary Search Function text: "def binary_search(arr, low, high, x):\n if high >= low:\n mid = (high + low) // 2\n if arr[mid] == x:\n return mid\n elif arr[mid] > x:\n" --- # BEE-spoke-data/beecoder-220M-python-GGUF Quantized GGUF model files for [beecoder-220M-python](https://huggingface.co/BEE-spoke-data/beecoder-220M-python) from [BEE-spoke-data](https://huggingface.co/BEE-spoke-data) | Name | Quant method | Size | | ---- | ---- | ---- | | [beecoder-220m-python.fp16.gguf](https://huggingface.co/afrideva/beecoder-220M-python-GGUF/resolve/main/beecoder-220m-python.fp16.gguf) | fp16 | 436.50 MB | | [beecoder-220m-python.q2_k.gguf](https://huggingface.co/afrideva/beecoder-220M-python-GGUF/resolve/main/beecoder-220m-python.q2_k.gguf) | q2_k | 94.43 MB | | [beecoder-220m-python.q3_k_m.gguf](https://huggingface.co/afrideva/beecoder-220M-python-GGUF/resolve/main/beecoder-220m-python.q3_k_m.gguf) | q3_k_m | 114.65 MB | | [beecoder-220m-python.q4_k_m.gguf](https://huggingface.co/afrideva/beecoder-220M-python-GGUF/resolve/main/beecoder-220m-python.q4_k_m.gguf) | q4_k_m | 137.58 MB | | [beecoder-220m-python.q5_k_m.gguf](https://huggingface.co/afrideva/beecoder-220M-python-GGUF/resolve/main/beecoder-220m-python.q5_k_m.gguf) | q5_k_m | 157.91 MB | | [beecoder-220m-python.q6_k.gguf](https://huggingface.co/afrideva/beecoder-220M-python-GGUF/resolve/main/beecoder-220m-python.q6_k.gguf) | q6_k | 179.52 MB | | [beecoder-220m-python.q8_0.gguf](https://huggingface.co/afrideva/beecoder-220M-python-GGUF/resolve/main/beecoder-220m-python.q8_0.gguf) | q8_0 | 232.28 MB | ## Original Model Card: # BEE-spoke-data/beecoder-220M-python This is `BEE-spoke-data/smol_llama-220M-GQA` fine-tuned for code generation on: - filtered version of stack-smol-XL - deduped version of 'algebraic stack' from proof-pile-2 - cleaned and deduped pypi (last dataset) This model (and the base model) were both trained using ctx length 2048. ## examples > Example script for inference testing: [here](https://gist.github.com/pszemraj/c7738f664a64b935a558974d23a7aa8c) It has its limitations at 220M, but seems decent for single-line or docstring generation, and/or being used for speculative decoding for such purposes. ![image/png](https://cdn-uploads.huggingface.co/production/uploads/60bccec062080d33f875cd0c/bLrtpr7Vi_MPvtF7mozDN.png) The screenshot is on CPU on a laptop. ---