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Model: omerkaragulmez/XbyK-0.1 Source: Original Platform
2026-06-15 02:06:16 +08:00
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+---
+license: apache-2.0
+base_model: mistralai/Mistral-Nemo-Instruct-2407
+tags:
+  - kentico
+  - xperience
+  - fine-tuned
+  - community
+  - multilingual
+language:
+  - en
+  - tr
+pipeline_tag: text-generation
+---
+
+# XbyK-0.1
+
+**XbyK-0.1** is a fine-tuned version of [mistralai/Mistral-Nemo-Instruct-2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407) specialized for **Xperience by Kentico** — a digital experience platform (DXP).
+
+> ⚠️ **This is not an official Kentico product.** XbyK-0.1 is a community-driven research project with no affiliation to Kentico a.s. It is not endorsed, sponsored, or maintained by Kentico. No commercial intent of any kind.
+
+---
+
+## Who we are?
+
+**As Portalgrup AI team,** we develop, build and maintane AI solutions.
+Portalgrup founded in 2007, PortalGrup entered the thriving internet ecosystem with a singular focus: creating and managing web portals. 
+But as time unfolded, our journey took an exhilarating turn. 
+We transformed into a versatile digital solutions provider, extending our reach across a diverse spectrum of services.
+
+Portalgrup website: [More detail](https://portalgrup.com)
+
+## Version: 0.1 — Why So Early?
+
+This model is at version **0.1** because its current evaluation results reflect meaningful room for improvement.
+
+Evaluated on 30 questions drawn from the official Kentico Xperience documentation, scored by **Qwen3:32b** as an independent judge (0–10 scale):
+
+| Metric | Result |
+|--------|--------|
+| Average score | **5.7 / 10** |
+| Score ≥ 7 rate | **40%** (12 / 30) |
+| Average response time | 1.4s |
+
+The 0.1 versioning is intentional and honest — the model is functional and useful for many queries, but there are known dataset quality issues that will be addressed in future iterations.
+
+---
+
+## Known Issues & Planned Improvements
+
+The following problems were identified through systematic evaluation and are documented here for full transparency:
+
+### Format Issues
+
+- **Question echo as heading** — Most responses start with `## {question text}` or `### {question text}`. This is caused by training examples where assistant answers included the question as a heading.  
+  *Fix: strip heading prefixes from all assistant turns in the training data.*
+
+- **One-sentence truncated answers** — Some responses end abruptly after a single sentence (e.g., *"Xperience gives you complete control over your content."*).  
+  *Fix: enforce minimum response depth in training examples.*
+
+### Factual Errors
+
+| Topic | Error |
+|-------|-------|
+| Headless draft vs. published | Model incorrectly states that draft items are accessible via the headless API — only **Published** items are |
+| Content sync — image variants | Model gave an irrelevant e-commerce paragraph instead of answering the actual question |
+| Automation license tier | Incomplete or incorrect license tier information |
+| Email channel license tier | Wrong license threshold stated |
+
+### Terminology Inconsistencies
+
+- Model uses "Asset tiles" instead of the correct term **"content item assets"**
+- Inconsistent usage of "Content Hub" vs. older naming conventions from previous Kentico versions
+
+### Weak Topic Coverage
+
+The following topics scored lowest and need additional training examples:
+
+| Topic | Issue |
+|-------|-------|
+| Pages vs. Content items | Core conceptual difference covered too superficially in training data |
+| Content sync — image variants | Too few specific examples in the dataset |
+| Headless draft / publish lifecycle | Frequently misunderstood; needs correct, emphatic examples |
+| License tier comparisons (Automation, Email) | License feature tables not well-represented in training data |
+| Smart Folder creation (step-by-step) | Procedural steps are missing from examples |
+
+---
+
+## Capabilities
+
+- **Chat**: Answer questions about Kentico Xperience development, content management, digital marketing, e-commerce, and best practices
+- **Multilingual**: English (primary) + inherited multilingual capabilities from Mistral-Nemo base
+
+## Training Data
+
+Fine-tuned on the official Kentico Xperience documentation:
+- [docs.kentico.com](https://docs.kentico.com/) — Documentation, guides, and training materials
+- [api-reference.kentico.com](https://api-reference.kentico.com/) — API reference
+
+The full training dataset is available at [omerkaragulmez/XbyK-0.1-dataset](https://huggingface.co/datasets/omerkaragulmez/XbyK-0.1-dataset).
+
+## Usage
+
+```python
+from transformers import pipeline
+
+pipe = pipeline("text-generation", model="omerkaragulmez/XbyK-0.1", torch_dtype="bfloat16", device_map="auto")
+
+messages = [
+    {"role": "user", "content": "How do I create a content type in Kentico Xperience?"}
+]
+
+response = pipe(messages, max_new_tokens=512, temperature=0.3)
+print(response[0]["generated_text"][-1]["content"])
+```
+
+### With Ollama (recommended)
+
+The quantized GGUF (`gguf/XbyK-0.1-Q4_K_M.gguf`) is available in this repo and can be used directly with Ollama:
+
+```bash
+ollama create xbyk-0.1 -f gguf/Modelfile
+ollama run xbyk-0.1 "How do I use the Delivery API?"
+```
+
+## Training Details
+
+- **Base model**: mistralai/Mistral-Nemo-Instruct-2407 (12B parameters)
+- **Method**: LoRA (Low-Rank Adaptation)
+- **Hardware**: 2× NVIDIA GH200
+- **Framework**: HuggingFace TRL + PEFT
+
+---
+
+## Disclaimer
+
+Xperience by Kentico™ is a registered trademark of Kentico a.s. This project is an independent community research effort and has no commercial intent. All documentation used for training is publicly available at docs.kentico.com