llm.create_chat_completion(
messages = "No input example has been defined for this model task."
)Zenith v0.1 — CMO Ready Agent (GGUF) by Zima Media
- Developed by: Zima Media
- License: apache-2.0
- Finetuned from model: unsloth/gemma-4-E2B-it
What is Zenith?
Zenith v0.1 is a CMO Ready Agent powered by the expertise of Mike Zima, Chief Marketing Officer at Zima Media.
This model captures Mike's deep knowledge across:
- Marketing strategy & planning — go-to-market, brand positioning, campaign architecture
- Sales prospecting & lead generation — B2B outreach, CRM workflows, data-driven acquisition
- Content marketing & storytelling — narrative frameworks, thought leadership, audience engagement
- Agency operations & client management — scaling services, team leadership, client success
Zenith is designed as a private AI tool for CMOs and growth leaders to safely test marketing ideas, strategy frameworks, and messaging without exposing sensitive data or relying on third-party models.
Why This Matters
Marketing is not broken. Your system is.
Most agencies sell channel execution. They don't build the systems that drive revenue. Zenith is built on a different philosophy — one system, one strategy, one outcome: profitable growth. No silos. No fragmentation. No channel-first thinking.
This is a CMO Ready Agent for leaders who want to:
- Test new marketing ideas privately before committing budget
- Validate strategy frameworks with an AI trained on real-world expertise
- Move faster without exposing sensitive data to external APIs
- Think bigger with a thinking partner that understands growth at scale
Training Data Breakdown
Zenith v0.1 was trained on a highly curated selection representing just 1% of our total available data — carefully chosen to capture the highest-signal content across Mike Zima's professional expertise. The remaining 99% was excluded to ensure quality, relevance, and a focused knowledge base.
The training corpus draws from the following sources:
| Source | Percentage of Training Data |
|---|---|
| LinkedIn posts & articles | 30% |
| Blog content & website copy | 25% |
| Internal strategy documents & playbooks | 20% |
| Presentations & slide decks | 15% |
| Video content (recordings, talks) | 10% |
Expertise Areas Covered
The model was fine-tuned on Mike Zima's deep knowledge across:
- Marketing strategy & planning — go-to-market frameworks, brand positioning, campaign architecture, budget allocation
- Sales prospecting & lead generation — B2B outreach strategies, CRM workflows, data-driven acquisition, list building
- Content marketing & storytelling — narrative frameworks, thought leadership, audience engagement, SEO content strategy
- Agency operations & client management — scaling services, team leadership, client success frameworks, pricing models
- Growth marketing & performance — paid media strategy, conversion optimization, analytics-driven decision making
- Brand development — brand identity, messaging architecture, competitive differentiation
DIY Installation Guide (macOS & Linux)
Getting Zenith up and running locally is straightforward. Here's how to install it for the first time:
Step 1: Download LM Studio
The easiest way to run Zenith locally is by using LM Studio. It provides a clean, private interface for chatting with AI without needing complex technical setup.
- Visit LM Studio and download the installer for your operating system (macOS or Linux).
- Install and launch the application.
Step 2: Search and Download Zenith
Inside LM Studio, you can pull the model weights directly from the cloud:
- Open the Search tab (magnifying glass icon).
- Type
zimamedia/zenith-v0.1-GGUFinto the search bar. - Find the model in the list and click Download next to the
zenith-v0.1-Q4_K_M.gguffile.
Step 3: Load & Run the Model
Once the download is complete:
- Go to the AI Chat tab (speech bubble icon).
- At the top of the screen, select the Zenith model from the dropdown menu.
- Critical Pro Tip: On the right-hand sidebar under Hardware Settings, ensure GPU Offload is set to Max. This will use your Mac's GPU cores for blazing-fast responses.
That's it. You now have a private, local CMO Ready Agent running on your machine.
Credits
- This model was originally trained using Unsloth and Hugging Face's TRL library.
- Quantized into GGUF format for universal compatibility.
- Built with ❤️ by Zima Media — The Revenue Engine for eCommerce Leaders.
- Downloads last month
- 103
4-bit
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="zimamedia/zenith-v0.1-q4_k_m", filename="zenith-v0.1-Q4_K_M.gguf", )