en pipeline_tag: text-generation tags:
esper
esper-2
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
dev-ops
terraform
azure
aws
gcp
architect
engineer
developer
conversational
chat
instruct base_model: meta-llama/Llama-3.2-3B-Instruct datasets:
sequelbox/Titanium
sequelbox/Tachibana
sequelbox/Supernova model-index:
name: ValiantLabs/Llama3.2-3B-Esper2 results:
- task: type: text-generation name: Text Generation dataset: name: Winogrande (5-Shot) type: Winogrande args: num_few_shot: 5 metrics:
  - type: acc value: 65.27 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: 43.17 name: normalized accuracy model_type: llama license: llama3.2

Esper 2 is a DevOps and cloud architecture code specialist built on Llama 3.2 3b.

Expertise-driven, an AI assistant focused on AWS, Azure, GCP, Terraform, Dockerfiles, pipelines, shell scripts and more!
Real world problem solving and high quality code instruct performance within the Llama 3.2 Instruct chat format
Finetuned on synthetic DevOps-instruct and code-instruct data generated with Llama 3.1 405b.
Overall chat performance supplemented with generalist chat data.

Try our code-instruct AI assistant Enigma!

Version

This is the 2024-10-03 release of Esper 2 for Llama 3.2 3b.

Esper 2 is also available for Llama 3.1 8b!

Esper 2 will be coming to more model sizes soon :)

Prompting Guide

Esper 2 uses the Llama 3.2 Instruct prompt format. The example script below can be used as a starting point for general chat:

python

import transformers
import torch

model_id = "ValiantLabs/Llama3.2-3B-Esper2"

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

messages = [
    {"role": "system", "content": "You are an AI assistant."},
    {"role": "user", "content": "Hi, how do I optimize the size of a Docker image?"}
]

outputs = pipeline(
    messages,
    max_new_tokens=2048,
)

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

The Model

Esper 2 is built on top of Llama 3.2 3b Instruct, improving performance through high quality DevOps, code, and chat data in Llama 3.2 Instruct prompt style.

Our current version of Esper 2 is trained on DevOps data from sequelbox/Titanium, supplemented by code-instruct data from sequelbox/Tachibana and general chat data from sequelbox/Supernova.

Esper 2 is created by Valiant Labs.

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

We care about open source. For everyone to use.

We encourage others to finetune further from our models.

RichardErkhov/ValiantLabs_-_Llama3.2-3B-Esper2-8bits

Original model description:

Version

Prompting Guide

The Model

RichardErkhov/
ValiantLabs_-_Llama3.2-3B-Esper2-8bits