File size: 3,813 Bytes
b4be6dd |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 |
---
license: apache-2.0
base_model: BEE-spoke-data/beecoder-220M-python
datasets:
- BEE-spoke-data/pypi_clean-deduped
- bigcode/the-stack-smol-xl
- EleutherAI/proof-pile-2
language:
- en
tags:
- python
- codegen
- markdown
- smol_llama
- llama-cpp
- gguf-my-repo
metrics:
- accuracy
inference:
parameters:
max_new_tokens: 64
min_new_tokens: 8
do_sample: true
epsilon_cutoff: 0.0008
temperature: 0.3
top_p: 0.9
repetition_penalty: 1.02
no_repeat_ngram_size: 8
renormalize_logits: true
widget:
- text: "def add_numbers(a, b):\n return\n"
example_title: Add Numbers Function
- 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: Car Class
- text: 'import pandas as pd
data = {''Name'': [''Tom'', ''Nick'', ''John''], ''Age'': [20, 21, 19]}
df = pd.DataFrame(data).convert_dtypes()
# eda
'
example_title: Pandas DataFrame
- text: "def factorial(n):\n if n == 0:\n return 1\n else:\n"
example_title: Factorial 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: Fibonacci Function
- text: 'import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0, 10, 100)
# simple plot
'
example_title: Matplotlib Plot
- text: "def reverse_string(s:str) -> str:\n return\n"
example_title: Reverse String Function
- text: "def is_palindrome(word:str) -> bool:\n return\n"
example_title: Palindrome 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: Bubble Sort 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"
example_title: Binary Search Function
pipeline_tag: text-generation
---
# ysn-rfd/beecoder-220M-python-Q8_0-GGUF
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.
Refer to the [original model card](https://huggingface.co/BEE-spoke-data/beecoder-220M-python) for more details on the model.
## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
```bash
brew install llama.cpp
```
Invoke the llama.cpp server or the CLI.
### CLI:
```bash
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"
```
### Server:
```bash
llama-server --hf-repo ysn-rfd/beecoder-220M-python-Q8_0-GGUF --hf-file beecoder-220m-python-q8_0.gguf -c 2048
```
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.
Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```
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).
```
cd llama.cpp && LLAMA_CURL=1 make
```
Step 3: Run inference through the main binary.
```
./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"
```
or
```
./llama-server --hf-repo ysn-rfd/beecoder-220M-python-Q8_0-GGUF --hf-file beecoder-220m-python-q8_0.gguf -c 2048
```
|