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Quantization made by Richard Erkhov.
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mega-ar-126m-4k - bnb 8bits
- Model creator: https://huggingface.co/BEE-spoke-data/
- Original model: https://huggingface.co/BEE-spoke-data/mega-ar-126m-4k/
Original model description:
---
license: apache-2.0
datasets:
- JeanKaddour/minipile
- BEE-spoke-data/wikipedia-20230901.en-deduped
- BEE-spoke-data/knowledge-inoc-concat-v1
language:
- en
inference:
parameters:
max_new_tokens: 64
do_sample: true
temperature: 0.8
repetition_penalty: 1.05
no_repeat_ngram_size: 4
epsilon_cutoff: 0.0006
renormalize_logits: true
widget:
- text: My name is El Microondas the Wise, and
example_title: El Microondas
- text: Kennesaw State University is a public
example_title: Kennesaw State University
- 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: Bungie
- text: The Mona Lisa is a world-renowned painting created by
example_title: Mona Lisa
- text: >-
The Harry Potter series, written by J.K. Rowling, begins with the book
titled
example_title: Harry Potter Series
- 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: Riddle
- text: The process of photosynthesis involves the conversion of
example_title: Photosynthesis
- 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: Story Continuation
- 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: Math Problem
- text: In the context of computer programming, an algorithm is
example_title: Algorithm Definition
pipeline_tag: text-generation
---
# BEE-spoke-data/mega-ar-126m-4k
This may not be the _best_ language model, but it is a language model! It's interesting for several reasons, not the least of which is that it's not technically a transformer.
Details:
- 768 hidden size, 12 layers
- no MEGA chunking, 4096 context length
- EMA dimension 16, shared dimension 192
- tokenizer: GPT NeoX
- train-from-scratch
For more info on MEGA (_& what some of the params above mean_), check out the [model docs](https://huggingface.co/docs/transformers/main/en/model_doc/mega#mega) or the [original paper](https://arxiv.org/abs/2209.10655)
## Usage
Usage is the same as any other small textgen model.
Given the model's small size and architecture, it's probably best to leverage its longer context by adding input context to "see more" rather than "generate more".
## evals
Initial data:
`hf-causal-experimental (pretrained=BEE-spoke-data/mega-ar-126m-4k,revision=main,trust_remote_code=True,dtype='float'), limit: None, provide_description: False, num_fewshot: 0, batch_size: 4`
| Task |Version| Metric | Value | |Stderr|
|--------------|------:|--------|------:|---|-----:|
|arc_easy | 0|acc | 0.4415|± |0.0102|
| | |acc_norm| 0.3969|± |0.0100|
|boolq | 1|acc | 0.5749|± |0.0086|
|lambada_openai| 0|ppl |94.9912|± |3.9682|
| | |acc | 0.2408|± |0.0060|
|openbookqa | 0|acc | 0.1660|± |0.0167|
| | |acc_norm| 0.2780|± |0.0201|
|piqa | 0|acc | 0.5974|± |0.0114|
| | |acc_norm| 0.5914|± |0.0115|
|winogrande | 0|acc | 0.4830|± |0.0140|
---
|