Using Alpaca 7B on Together AI
Implementation guide · Alpaca · Stanford ArtificiaI Intelligence Laboratory (SAIL)
Quick Start
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Code Examples
pip install togetherTOGETHER_API_KEYalpaca-7bTogether 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="alpaca-7b",
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
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.20 |
Capabilities
About Alpaca 7B
Alpaca 7B is a language model developed by Stanford University, derived from Meta's LLaMA 7B, designed for instruction-following tasks. It excels in producing coherent, context-sensitive responses and is comparable to OpenAI's text-davinci-003, despite its smaller size and lower training costs. With a transformer-based architecture of 7 billion parameters, it efficiently balances performance and resource needs, suitable for devices like laptops. Trained on 52,000 instruction-based demonstrations, it offers high-quality interaction while facing challenges like hallucination and stereotyping, indicating a need for careful real-world application.