Meltemi-llamafile / README.md
Florents-Tselai's picture
Update README.md
4385359 verified
|
raw
history blame
2.41 kB
metadata
language:
  - el
  - en
license: apache-2.0
pipeline_tag: text-generation
tags:
  - finetuned
inference: true
base_model:
  - ilsp/Meltemi-7B-Instruct-v1.5

Meltemi llamafile & gguf

This repo contains llamafile and gguf file format models for Meltemi 7B Instract v1.5, the first Greek Large Language Model (LLM)

lamafile is a file format introduced by Mozilla Ocho on Nov 20th 2023, and it collapses the complexity of an LLM into a single executable file. This gives you the easiest, fastest way to use Meltemi on Linux, MacOS, Windows, FreeBSD, OpenBSD, and NetBSD systems you control on both AMD64 and ARM64.

It's as simple as this

wget https://huggingface.co/Florents-Tselai/Meltemi-llamafile/resolve/main/Meltemi-7B-Instruct-v1.5-Q8_0.llamafile
chmod +x Meltemi-7B-Instruct-v1.5-Q8_0.llamafile
./Meltemi-7B-Instruct-v1.5-Q8_0.llamafile

This will open a tab with a chatbot and completion interface in your browser. For additional help on how it may be used, pass the --help flag. The server also has an OpenAI API-compatible completions endpoint.

An advanced CLI mode is provided that's useful for shell scripting. You can use it by passing the --cli flag. For additional help on how it may be used, pass the --help flag.

./Meltemi-7B-Instruct-v1.5-Q8_0.llamafile -p 'Ποιό είναι το νόημα της ζωής;'

To see all available options

./Meltemi-7B-Instruct-v1.5-Q8_0.llamafile --help

gguf

gguf file formats are also available if you're working with llama.cpp llama.cpp

llama.cpp offers quite a lot of options, thus refer to its documentation.

Basic Usage

llama-cli -m ./Meltemi-7B-Instruct-v1.5-F16.gguf -p "Ποιό είναι το νόημα της ζωής;" -n 128

Conversation Mode

llama-cli -m ./Meltemi-7B-Instruct-v1.5-F16.gguf --conv 

Web Server

llama-server -m ./Meltemi-7B-Instruct-v1.5-F16.gguf --port 8080

Model Information

  • Vocabulary extension of the Mistral 7b tokenizer with Greek tokens for lower costs and faster inference (1.52 vs. 6.80 tokens/word for Greek)
  • 8192 context length

For more details, please refer to the original model card Meltemi 7B Instract v1.5