Using Zephyr 7B Beta on Replicate API
Implementation guide · Zephyr · Hugging Face H4
Replicate API exposes Zephyr 7B Beta through model ID nateraw/zephyr-7b-beta. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-09-30. Next refresh: weekly.
Quick Start
- 1
- 2Use the Replicate API SDK or REST API to call
nateraw/zephyr-7b-beta— see the documentation for request format. - 3
Code Examples
pip install replicateREPLICATE_API_TOKENnateraw/zephyr-7b-betaReplicate uses "owner/model-name" format (e.g. "meta/meta-llama-3-8b-instruct") for the latest version, or "owner/model-name:version-sha" to pin to a specific version. The REST endpoint splits owner and model-name into the path: /v1/models/{owner}/{model-name}/predictions.
import replicate
# reads REPLICATE_API_TOKEN from env
# nateraw/zephyr-7b-beta format: "owner/model-name" (latest version) or "owner/model-name:version-hash"
output = replicate.run(
"nateraw/zephyr-7b-beta",
input={"prompt": "Hello"}
)
# Output is a list or generator depending on the model
print("".join(output))Pricing on Replicate API
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.05 |
| Output tokens | $0.25 |
Capabilities
No model capability flags are currently sourced.
About Zephyr 7B Beta
Zephyr 7B Beta is a 7-billion parameter large language model, fine-tuned from the Mistral-7B-v0.1 model. It is tailored to serve as an effective virtual assistant, performing well in generating human-like responses. The model's training involved Direct Preference Optimization (DPO) on a combination of publicly available and synthetic datasets, achieving strong performance on benchmarks like MT-Bench and AlpacaEval, especially for conversational tasks. However, its complexity falls short when compared to proprietary models, especially in tasks involving coding and mathematics. A notable limitation is its insufficient alignment to human safety preferences and the absence of in-the-loop filtering to prevent problematic outputs.