metadata

base_model: BEE-spoke-data/smol_llama-101M-GQA
datasets:
  - JeanKaddour/minipile
  - pszemraj/simple_wikipedia_LM
  - BEE-spoke-data/wikipedia-20230901.en-deduped
  - mattymchen/refinedweb-3m
inference: false
language:
  - en
license: apache-2.0
model_creator: BEE-spoke-data
model_name: smol_llama-101M-GQA
pipeline_tag: text-generation
quantized_by: afrideva
tags:
  - smol_llama
  - llama2
  - gguf
  - ggml
  - quantized
  - q2_k
  - q3_k_m
  - q4_k_m
  - q5_k_m
  - q6_k
  - q8_0
thumbnail: https://i.ibb.co/TvyMrRc/rsz-smol-llama-banner.png
widget:
  - example_title: El Microondas
    text: My name is El Microondas the Wise and
  - example_title: Kennesaw State University
    text: Kennesaw State University is a public
  - example_title: Bungie
    text: >-
      Bungie Studios is an American video game developer. They are most famous
      for developing the award winning Halo series of video games. They also
      made Destiny. The studio was founded
  - example_title: Mona Lisa
    text: The Mona Lisa is a world-renowned painting created by
  - example_title: Harry Potter Series
    text: >-
      The Harry Potter series, written by J.K. Rowling, begins with the book
      titled
  - example_title: Riddle
    text: >-
      Question: I have cities, but no houses. I have mountains, but no trees. I
      have water, but no fish. What am I?

      Answer:
  - example_title: Photosynthesis
    text: The process of photosynthesis involves the conversion of
  - example_title: Story Continuation
    text: >-
      Jane went to the store to buy some groceries. She picked up apples,
      oranges, and a loaf of bread. When she got home, she realized she forgot
  - example_title: Math Problem
    text: >-
      Problem 2: If a train leaves Station A at 9:00 AM and travels at 60 mph,
      and another train leaves Station B at 10:00 AM and travels at 80 mph, when
      will they meet if the distance between the stations is 300 miles?

      To determine
  - example_title: Algorithm Definition
    text: In the context of computer programming, an algorithm is

BEE-spoke-data/smol_llama-101M-GQA-GGUF

Quantized GGUF model files for smol_llama-101M-GQA from BEE-spoke-data

Name	Quant method	Size
smol_llama-101m-gqa.fp16.gguf	fp16	203.28 MB
smol_llama-101m-gqa.q2_k.gguf	q2_k	50.93 MB
smol_llama-101m-gqa.q3_k_m.gguf	q3_k_m	57.06 MB
smol_llama-101m-gqa.q4_k_m.gguf	q4_k_m	65.40 MB
smol_llama-101m-gqa.q5_k_m.gguf	q5_k_m	74.34 MB
smol_llama-101m-gqa.q6_k.gguf	q6_k	83.83 MB
smol_llama-101m-gqa.q8_0.gguf	q8_0	108.35 MB

Original Model Card:

smol_llama-101M-GQA

A small 101M param (total) decoder model. This is the first version of the model.

768 hidden size, 6 layers
GQA (24 heads, 8 key-value), context length 1024
train-from-scratch

Notes

This checkpoint is the 'raw' pre-trained model and has not been tuned to a more specific task. It should be fine-tuned before use in most cases.

Checkpoints & Links

smol-er 81M parameter checkpoint with in/out embeddings tied: here
Fine-tuned on pypi to generate Python code - link
For the chat version of this model, please see here

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	25.32
ARC (25-shot)	23.55
HellaSwag (10-shot)	28.77
MMLU (5-shot)	24.24
TruthfulQA (0-shot)	45.76
Winogrande (5-shot)	50.67
GSM8K (5-shot)	0.83
DROP (3-shot)	3.39