smol_llama-81M-tied/README.md

license, thumbnail, language, inference, widget, pipeline_tag, tags, datasets

license	thumbnail	language	inference	widget	pipeline_tag	tags	datasets
apache-2.0	https://i.ibb.co/TvyMrRc/rsz-smol-llama-banner.png	en	parameters max_new_tokens do_sample temperature repetition_penalty no_repeat_ngram_size eta_cutoff renormalize_logits 64 true 0.8 1.15 4 0.0006 true	text example_title My name is El Microondas the Wise and El Microondas text example_title Kennesaw State University is a public Kennesaw State University text example_title 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 Bungie text example_title The Mona Lisa is a world-renowned painting created by Mona Lisa text example_title The Harry Potter series, written by J.K. Rowling, begins with the book titled Harry Potter Series text example_title Question: I have cities, but no houses. I have mountains, but no trees. I have water, but no fish. What am I? Answer: Riddle text example_title The process of photosynthesis involves the conversion of Photosynthesis text example_title 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 Story Continuation text example_title 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 Math Problem text example_title In the context of computer programming, an algorithm is Algorithm Definition	text-generation	smol_llama llama2	JeanKaddour/minipile pszemraj/simple_wikipedia_LM BEE-spoke-data/wikipedia-20230901.en-deduped mattymchen/refinedweb-3m

smol_llama-81M-tied

A small 81M param (total) decoder model, enabled through tying the input/output embeddings. This is the first version of the model.

• 768 hidden size, 6 layers
• standard multi-head attention (24 heads), context length 1024
• input/output embeddings are tied
• 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.

• slightly larger 101M param GQA pretrained version: here
• For the chat version of this model, please see here

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Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	24.52
ARC (25-shot)	22.18
HellaSwag (10-shot)	29.33
MMLU (5-shot)	24.06
TruthfulQA (0-shot)	43.97
Winogrande (5-shot)	49.25
GSM8K (5-shot)	0.23
DROP (3-shot)	2.64