Llama3.1-8B-Cobalt / README.md
sequelbox's picture
model card
9c7aa65 verified
|
raw
history blame
No virus
2.62 kB
metadata
language:
  - en
pipeline_tag: text-generation
tags:
  - cobalt
  - 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
  - math
  - math-instruct
  - conversational
  - chat
  - instruct
model_type: llama
license: llama3.1

Cobalt is a math-instruct model built on Llama 3.1 8b

Version

This is the 2024-08-16 release of Cobalt for Llama 3.1 8b.

Help us and recommend Cobalt to your friends! We're excited for more Cobalt 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

Cobalt 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-Cobalt"

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

messages = [ {"role": "system", "content": "You are Cobalt, expert math AI."}, {"role": "user", "content": "I'm buying a $50 shirt and a $80 pair of pants, both currently at a 25% discount. How much will I pay?"} ]

outputs = pipeline( messages, max_new_tokens=1024, )

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

The Model

Cobalt is built on top of Llama 3.1 8b Instruct, using math-instruct data to supplement math-instruct performance using Llama 3.1 Instruct prompt style.

Our current version of the Cobalt math-instruct dataset is sequelbox/Polytope, supplemented with a small selection of data from LDJnr/Pure-Dove for general chat consistency.

image/jpeg

Cobalt 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.