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Using WizardCoder Python 34B on Together AI

Implementation guide · WizardCoder · WizardLM Team

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 wizardcoder-python-34b — see the documentation for request format.
  3. 3
    You'll be billed $0.80/1M input, $0.80/1M output tokens. See full pricing.

Code Examples

Install
pip install together
API key
TOGETHER_API_KEY
Model ID
wizardcoder-python-34b

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="wizardcoder-python-34b",
    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$0.80
Output tokens$0.80

Capabilities

Structured Outputs

About WizardCoder Python 34B

WizardCoder Python 34B is a large language model (LLM) tailored for code generation and comprehension, primarily focusing on Python. Harnessing a Transformer-based structure with 34 billion parameters, it was refined using the Evol-Instruct method to enhance its instruction-following skills. This model excels in generating accurate and context-aware code, offering functionalities like code generation, completion, summarization, and translation across languages. It has achieved notable performance in benchmarks such as HumanEval, even outperforming certain versions of GPT-4 in specific tests. Despite its strengths, it requires significant computational resources, such as at least 32GB of RAM, for optimal performance and has different quantization levels to balance accuracy and resource needs 146.

Model Specs

Released2024-01-29
Parameters34B
Context100K
ArchitectureDecoder Only

Provider

Together AI
Together AI

San Francisco, California, United States