language:
- en
license: llama3.2
tags:
- enigma
- valiant
- valiant-labs
- llama
- llama-3.2
- llama-3.2-instruct
- llama-3.2-instruct-3b
- llama-3
- llama-3-instruct
- llama-3-instruct-3b
- 3b
- code
- code-instruct
- python
- conversational
- chat
- instruct
base_model: meta-llama/Llama-3.2-3B-Instruct
datasets:
- sequelbox/Tachibana
- sequelbox/Supernova
pipeline_tag: text-generation
model_type: llama
model-index:
- name: Llama3.2-3B-Enigma
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-Shot)
type: winogrande
args:
num_few_shot: 5
metrics:
- type: acc
value: 67.96
name: acc
- task:
type: text-generation
name: Text Generation
dataset:
name: ARC Challenge (25-Shot)
type: arc-challenge
args:
num_few_shot: 25
metrics:
- type: acc_norm
value: 47.18
name: normalized accuracy
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 47.75
name: strict accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.2-3B-Enigma
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 18.81
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.2-3B-Enigma
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 6.65
name: exact match
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.2-3B-Enigma
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 1.45
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.2-3B-Enigma
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 4.54
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.2-3B-Enigma
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 15.41
name: accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ValiantLabs/Llama3.2-3B-Enigma
name: Open LLM Leaderboard
QuantFactory/Llama3.2-3B-Enigma-GGUF
This is quantized version of ValiantLabs/Llama3.2-3B-Enigma created using llama.cpp
Original Model Card
Enigma is a code-instruct model built on Llama 3.2 3b.
- High quality code instruct performance with the Llama 3.2 Instruct chat format
- Finetuned on synthetic code-instruct data generated with Llama 3.1 405b. Find the current version of the dataset here!
- Overall chat performance supplemented with generalist synthetic data.
Version
This is the 2024-09-30 release of Enigma for Llama 3.2 3b, enhancing code-instruct and general chat capabilities.
Enigma is also available for Llama 3.1 8b!
Help us and recommend Enigma to your friends! We're excited for more Enigma releases in the future.
Prompting Guide
Enigma uses the Llama 3.2 Instruct prompt format. The example script below can be used as a starting point for general chat:
import transformers
import torch
model_id = "ValiantLabs/Llama3.2-3B-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 3.2 3b Instruct, using high quality code-instruct data and general chat data in Llama 3.2 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.
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.