File size: 6,656 Bytes

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---
license: apache-2.0
thumbnail: https://i.ibb.co/TvyMrRc/rsz-smol-llama-banner.png
language:
- en
inference:
  parameters:
    max_new_tokens: 64
    do_sample: true
    temperature: 0.8
    repetition_penalty: 1.15
    no_repeat_ngram_size: 4
    eta_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
tags:
- smol_llama
- llama2
- TensorBlock
- GGUF
datasets:
- JeanKaddour/minipile
- pszemraj/simple_wikipedia_LM
- BEE-spoke-data/wikipedia-20230901.en-deduped
- mattymchen/refinedweb-3m
base_model: BEE-spoke-data/smol_llama-81M-tied
---

<div style="width: auto; margin-left: auto; margin-right: auto">
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</div>
<div style="display: flex; justify-content: space-between; width: 100%;">
    <div style="display: flex; flex-direction: column; align-items: flex-start;">
        <p style="margin-top: 0.5em; margin-bottom: 0em;">
            Feedback and support: TensorBlock's  <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
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## BEE-spoke-data/smol_llama-81M-tied - GGUF

This repo contains GGUF format model files for [BEE-spoke-data/smol_llama-81M-tied](https://huggingface.co/BEE-spoke-data/smol_llama-81M-tied).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).

<div style="text-align: left; margin: 20px 0;">
    <a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
        Run them on the TensorBlock client using your local machine ↗
    </a>
</div>

## Prompt template

```

```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [smol_llama-81M-tied-Q2_K.gguf](https://huggingface.co/tensorblock/smol_llama-81M-tied-GGUF/blob/main/smol_llama-81M-tied-Q2_K.gguf) | Q2_K | 0.039 GB | smallest, significant quality loss - not recommended for most purposes |
| [smol_llama-81M-tied-Q3_K_S.gguf](https://huggingface.co/tensorblock/smol_llama-81M-tied-GGUF/blob/main/smol_llama-81M-tied-Q3_K_S.gguf) | Q3_K_S | 0.042 GB | very small, high quality loss |
| [smol_llama-81M-tied-Q3_K_M.gguf](https://huggingface.co/tensorblock/smol_llama-81M-tied-GGUF/blob/main/smol_llama-81M-tied-Q3_K_M.gguf) | Q3_K_M | 0.045 GB | very small, high quality loss |
| [smol_llama-81M-tied-Q3_K_L.gguf](https://huggingface.co/tensorblock/smol_llama-81M-tied-GGUF/blob/main/smol_llama-81M-tied-Q3_K_L.gguf) | Q3_K_L | 0.047 GB | small, substantial quality loss |
| [smol_llama-81M-tied-Q4_0.gguf](https://huggingface.co/tensorblock/smol_llama-81M-tied-GGUF/blob/main/smol_llama-81M-tied-Q4_0.gguf) | Q4_0 | 0.049 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [smol_llama-81M-tied-Q4_K_S.gguf](https://huggingface.co/tensorblock/smol_llama-81M-tied-GGUF/blob/main/smol_llama-81M-tied-Q4_K_S.gguf) | Q4_K_S | 0.050 GB | small, greater quality loss |
| [smol_llama-81M-tied-Q4_K_M.gguf](https://huggingface.co/tensorblock/smol_llama-81M-tied-GGUF/blob/main/smol_llama-81M-tied-Q4_K_M.gguf) | Q4_K_M | 0.051 GB | medium, balanced quality - recommended |
| [smol_llama-81M-tied-Q5_0.gguf](https://huggingface.co/tensorblock/smol_llama-81M-tied-GGUF/blob/main/smol_llama-81M-tied-Q5_0.gguf) | Q5_0 | 0.056 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [smol_llama-81M-tied-Q5_K_S.gguf](https://huggingface.co/tensorblock/smol_llama-81M-tied-GGUF/blob/main/smol_llama-81M-tied-Q5_K_S.gguf) | Q5_K_S | 0.056 GB | large, low quality loss - recommended |
| [smol_llama-81M-tied-Q5_K_M.gguf](https://huggingface.co/tensorblock/smol_llama-81M-tied-GGUF/blob/main/smol_llama-81M-tied-Q5_K_M.gguf) | Q5_K_M | 0.057 GB | large, very low quality loss - recommended |
| [smol_llama-81M-tied-Q6_K.gguf](https://huggingface.co/tensorblock/smol_llama-81M-tied-GGUF/blob/main/smol_llama-81M-tied-Q6_K.gguf) | Q6_K | 0.063 GB | very large, extremely low quality loss |
| [smol_llama-81M-tied-Q8_0.gguf](https://huggingface.co/tensorblock/smol_llama-81M-tied-GGUF/blob/main/smol_llama-81M-tied-Q8_0.gguf) | Q8_0 | 0.081 GB | very large, extremely low quality loss - not recommended |


## Downloading instruction

### Command line

Firstly, install Huggingface Client

```shell
pip install -U "huggingface_hub[cli]"
```

Then, downoad the individual model file the a local directory

```shell
huggingface-cli download tensorblock/smol_llama-81M-tied-GGUF --include "smol_llama-81M-tied-Q2_K.gguf" --local-dir MY_LOCAL_DIR
```

If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:

```shell
huggingface-cli download tensorblock/smol_llama-81M-tied-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```