--- language: - 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 --- ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64f267a8a4f79a118e0fcc89/4I6oK8DG0so4VD8GroFsd.jpeg) 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](https://huggingface.co/datasets/sequelbox/Titanium) and [code-instruct](https://huggingface.co/datasets/sequelbox/Tachibana) data generated with Llama 3.1 405b. - Overall chat performance supplemented with [generalist chat data.](https://huggingface.co/datasets/sequelbox/Supernova) Try our code-instruct AI assistant [Enigma!](https://huggingface.co/ValiantLabs/Llama3.1-8B-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!](https://huggingface.co/ValiantLabs/Llama3.1-8B-Esper2) Esper 2 will be coming to more model sizes soon :) ## Prompting Guide Esper 2 uses the [Llama 3.2 Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-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](https://huggingface.co/datasets/sequelbox/Titanium), supplemented by code-instruct data from [sequelbox/Tachibana](https://huggingface.co/datasets/sequelbox/Tachibana) and general chat data from [sequelbox/Supernova.](https://huggingface.co/datasets/sequelbox/Supernova) ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/63444f2687964b331809eb55/VCJ8Fmefd8cdVhXSSxJiD.jpeg) Esper 2 is created by [Valiant Labs.](http://valiantlabs.ca/) [Check out our HuggingFace page for Shining Valiant 2, Enigma, and our other Build Tools models for creators!](https://huggingface.co/ValiantLabs) [Follow us on X for updates on our models!](https://twitter.com/valiant_labs) We care about open source. For everyone to use. We encourage others to finetune further from our models.