Llama3.1-8B-Enigma / README.md
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metadata
language:
  - en
pipeline_tag: text-generation
tags:
  - enigma
  - valiant
  - valiant-labs
  - llama
  - llama-3.1
  - llama-3.1-instruct
  - llama-3.1-instruct-8b
  - llama-3
  - llama-3-instruct
  - llama-3-instruct-8b
  - 8b
  - code
  - code-instruct
  - python
  - conversational
  - chat
  - instruct
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
  - sequelbox/Tachibana
  - sequelbox/Supernova
model_type: llama
license: llama3.1

image/jpeg

Enigma is a code-instruct model built on Llama 3.1 8b.

Version

This is the 2024-09-04 release of Enigma for Llama 3.1 8b, enhancing code-instruct and general chat capabilities.

Help us and recommend Enigma to your friends! We're excited for more Enigma releases in the future.

Right now, we're working on more new Build Tools to come very soon, built on Llama 3.1 :)

Prompting Guide

Enigma uses the Llama 3.1 Instruct prompt format. The example script below can be used as a starting point for general chat:

import transformers
import torch

model_id = "ValiantLabs/Llama3.1-8B-Enigma"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

messages = [
    {"role": "system", "content": "You are Enigma, a highly capable code assistant."},
    {"role": "user", "content": "Can you explain virtualization to me?"}
]

outputs = pipeline(
    messages,
    max_new_tokens=1024,
)

print(outputs[0]["generated_text"][-1])

The Model

Enigma is built on top of Llama 3.1 8b Instruct, using high quality code-instruct data and general chat data in Llama 3.1 Instruct prompt style to supplement overall performance.

Our current version of Enigma is trained on code-instruct data from sequelbox/Tachibana and general chat data from sequelbox/Supernova.

image/jpeg

Enigma is created by Valiant Labs.

Check out our HuggingFace page for Shining Valiant 2 and our other Build Tools models for creators!

Follow us on X for updates on our models!

We care about open source. For everyone to use.

We encourage others to finetune further from our models.