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smol_llama-81M-tied-GGUF

Text Generation
GGUF
English
smol_llama
llama2
TensorBlock
GGUF
Inference Endpoints
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metadata
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
TensorBlock

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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.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

Prompt template

Model file specification

Filename Quant type File Size Description
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 Q3_K_S 0.042 GB very small, high quality loss
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 Q3_K_L 0.047 GB small, substantial quality loss
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 Q4_K_S 0.050 GB small, greater quality loss
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 Q5_0 0.056 GB legacy; medium, balanced quality - prefer using Q4_K_M
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 Q5_K_M 0.057 GB large, very low quality loss - recommended
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 Q8_0 0.081 GB very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

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:

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