BEE-spoke-data/beecoder-220M-python
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1---2license: apache-2.03base_model: BEE-spoke-data/smol_llama-220M-GQA4datasets:5- BEE-spoke-data/pypi_clean-deduped6- bigcode/the-stack-smol-xl7- EleutherAI/proof-pile-28language:9- en10tags:11- python12- codegen13- markdown14- smol_llama15metrics:16- accuracy17inference:18 parameters:19 max_new_tokens: 6420 min_new_tokens: 821 do_sample: true22 epsilon_cutoff: 0.000823 temperature: 0.324 top_p: 0.925 repetition_penalty: 1.0226 no_repeat_ngram_size: 827 renormalize_logits: true28widget:29- text: |30 def add_numbers(a, b):31 return32 example_title: Add Numbers Function33- text: |34 class Car:35 def __init__(self, make, model):36 self.make = make37 self.model = model38 39 def display_car(self):40 example_title: Car Class41- text: |42 import pandas as pd43 data = {'Name': ['Tom', 'Nick', 'John'], 'Age': [20, 21, 19]}44 df = pd.DataFrame(data).convert_dtypes()45 # eda46 example_title: Pandas DataFrame47- text: |48 def factorial(n):49 if n == 0:50 return 151 else:52 example_title: Factorial Function53- text: |54 def fibonacci(n):55 if n <= 0:56 raise ValueError("Incorrect input")57 elif n == 1:58 return 059 elif n == 2:60 return 161 else:62 example_title: Fibonacci Function63- text: |64 import matplotlib.pyplot as plt65 import numpy as np66 x = np.linspace(0, 10, 100)67 # simple plot68 example_title: Matplotlib Plot69- text: |70 def reverse_string(s:str) -> str:71 return72 example_title: Reverse String Function73- text: |74 def is_palindrome(word:str) -> bool:75 return76 example_title: Palindrome Function77- text: |78 def bubble_sort(lst: list):79 n = len(lst)80 for i in range(n):81 for j in range(0, n-i-1):82 example_title: Bubble Sort Function83- text: |84 def binary_search(arr, low, high, x):85 if high >= low:86 mid = (high + low) // 287 if arr[mid] == x:88 return mid89 elif arr[mid] > x:90 example_title: Binary Search Function91pipeline_tag: text-generation92---93 94# BEE-spoke-data/beecoder-220M-python95 96 97 98 99This is `BEE-spoke-data/smol_llama-220M-GQA` fine-tuned for code generation on:100 101- filtered version of stack-smol-XL102- deduped version of 'algebraic stack' from proof-pile-2103- cleaned and deduped pypi (last dataset)104 105This model (and the base model) were both trained using ctx length 2048. 106 107## examples108 109> Example script for inference testing: [here](https://gist.github.com/pszemraj/c7738f664a64b935a558974d23a7aa8c)110 111It has its limitations at 220M, but seems decent for single-line or docstring generation, and/or being used for speculative decoding for such purposes.112 113 114 115116 117The screenshot is on CPU on a laptop.118 119---