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README.md

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+---
+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](https://huggingface.co/BEE-spoke-data/smol_llama-101M-GQA) from [BEE-spoke-data](https://huggingface.co/BEE-spoke-data)
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [smol_llama-101m-gqa.fp16.gguf](https://huggingface.co/afrideva/smol_llama-101M-GQA-GGUF/resolve/main/smol_llama-101m-gqa.fp16.gguf) | fp16 | 203.28 MB  |
+| [smol_llama-101m-gqa.q2_k.gguf](https://huggingface.co/afrideva/smol_llama-101M-GQA-GGUF/resolve/main/smol_llama-101m-gqa.q2_k.gguf) | q2_k | 50.93 MB  |
+| [smol_llama-101m-gqa.q3_k_m.gguf](https://huggingface.co/afrideva/smol_llama-101M-GQA-GGUF/resolve/main/smol_llama-101m-gqa.q3_k_m.gguf) | q3_k_m | 57.06 MB  |
+| [smol_llama-101m-gqa.q4_k_m.gguf](https://huggingface.co/afrideva/smol_llama-101M-GQA-GGUF/resolve/main/smol_llama-101m-gqa.q4_k_m.gguf) | q4_k_m | 65.40 MB  |
+| [smol_llama-101m-gqa.q5_k_m.gguf](https://huggingface.co/afrideva/smol_llama-101M-GQA-GGUF/resolve/main/smol_llama-101m-gqa.q5_k_m.gguf) | q5_k_m | 74.34 MB  |
+| [smol_llama-101m-gqa.q6_k.gguf](https://huggingface.co/afrideva/smol_llama-101M-GQA-GGUF/resolve/main/smol_llama-101m-gqa.q6_k.gguf) | q6_k | 83.83 MB  |
+| [smol_llama-101m-gqa.q8_0.gguf](https://huggingface.co/afrideva/smol_llama-101M-GQA-GGUF/resolve/main/smol_llama-101m-gqa.q8_0.gguf) | q8_0 | 108.35 MB  |
+
+
+
+## Original Model Card:
+# smol_llama-101M-GQA
+
+<img src="smol-llama-banner.png" alt="banner" style="max-width:95%; height:auto;">
+
+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](https://huggingface.co/BEE-spoke-data/smol_llama-81M-tied)
+- Fine-tuned on `pypi` to generate Python code - [link](https://huggingface.co/BEE-spoke-data/smol_llama-101M-GQA-python)
+- For the chat version of this model, please [see here](https://youtu.be/dQw4w9WgXcQ?si=3ePIqrY1dw94KMu4)
+
+---
+
+
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_BEE-spoke-data__smol_llama-101M-GQA)
+
+| 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         |