llmreference
Together AI

Using Platypus2 70B on Together AI

Implementation guide · Platypus2 · garage-bAInd

Serverless

Quick Start

  1. 1
    Create an account at Together AI and generate an API key.
  2. 2
    Use the Together AI SDK or REST API to call platypus2-70b — see the documentation for request format.
  3. 3
    You'll be billed $0.90/1M input, $0.90/1M output tokens. See full pricing.

Code Examples

Install
pip install together
API key
TOGETHER_API_KEY
Model ID
platypus2-70b

Together uses "organization/model-name" format, e.g. "meta-llama/Llama-4-Scout-17B-16E-Instruct" or "Qwen/QwQ-32B". See the Together model catalog for the exact ID.

from together import Together

client = Together()  # reads TOGETHER_API_KEY from env
response = client.chat.completions.create(
    model="platypus2-70b",
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

About Together AI

Platform for running open-source and proprietary LLMs

Together AI is a platform for running open-source and proprietary LLMs with fast serverless and dedicated endpoints at competitive inference pricing.

Pricing on Together AI

TypePrice (per 1M)
Input tokens$0.90
Output tokens$0.90

Capabilities

Structured Outputs

About Platypus2 70B

Platypus2-70B is an advanced auto-regressive language model leveraging the LLaMA 2 transformer architecture, specifically designed by Cole Hunter and Ariel Lee. Distinguished for its exceptional capabilities in STEM and logic tasks, the model's proficiency is bolstered by its training on the Open-Platypus dataset, optimized using Low-Rank Adaptation (LoRA) and Parameter-Efficient Fine-Tuning (PEFT) techniques. This efficient training method enables performance optimization with fewer computational resources. Notably, Platypus2-70B once attained the top spot on HuggingFace's Open LLM Leaderboard, showcasing its robust performance across various benchmark metrics. It supports diverse applications in fields such as education and research, although continued emphasis on safety and bias testing remains crucial. The model emphasizes English language proficiency and offers quantized versions for varied hardware compatibility.

Model Specs

Released2023-12-15
Parameters70B
ArchitectureDecoder Only

Provider

Together AI
Together AI

San Francisco, California, United States