Filter by type:
Filter by tags:
nousresearch_hermes-4-14b
Hermes 4 14B is a frontier, hybrid-mode reasoning model based on Qwen 3 14B by Nous Research that is aligned to you.
Read the Hermes 4 technical report here: Hermes 4 Technical Report
Chat with Hermes in Nous Chat: https://chat.nousresearch.com
Training highlights include a newly synthesized post-training corpus emphasizing verified reasoning traces, massive improvements in math, code, STEM, logic, creativity, and format-faithful outputs, while preserving general assistant quality and broadly neutral alignment.
What’s new vs Hermes 3
Post-training corpus: Massively increased dataset size from 1M samples and 1.2B tokens to ~5M samples / ~60B tokens blended across reasoning and non-reasoning data.
Hybrid reasoning mode with explicit … segments when the model decides to deliberate, and options to make your responses faster when you want.
Reasoning that is top quality, expressive, improves math, code, STEM, logic, and even creative writing and subjective responses.
Schema adherence & structured outputs: trained to produce valid JSON for given schemas and to repair malformed objects.
Much easier to steer and align: extreme improvements on steerability, especially on reduced refusal rates.
Repository: localaiLicense: apache-2.0
nousresearch_hermes-4-70b
Hermes 4 70B is a frontier, hybrid-mode reasoning model based on Llama-3.1-70B by Nous Research that is aligned to you.
Read the Hermes 4 technical report here: Hermes 4 Technical Report
Chat with Hermes in Nous Chat: https://chat.nousresearch.com
Training highlights include a newly synthesized post-training corpus emphasizing verified reasoning traces, massive improvements in math, code, STEM, logic, creativity, and format-faithful outputs, while preserving general assistant quality and broadly neutral alignment.
What’s new vs Hermes 3
Post-training corpus: Massively increased dataset size from 1M samples and 1.2B tokens to ~5M samples / ~60B tokens blended across reasoning and non-reasoning data.
Hybrid reasoning mode with explicit … segments when the model decides to deliberate, and options to make your responses faster when you want.
Reasoning that is top quality, expressive, improves math, code, STEM, logic, and even creative writing and subjective responses.
Schema adherence & structured outputs: trained to produce valid JSON for given schemas and to repair malformed objects.
Much easier to steer and align: extreme improvements on steerability, especially on reduced refusal rates.
Repository: localaiLicense: llama3
thoughtless-fallen-abomination-70b-r1-v4.1-i1
ReadyArt/Thoughtless-Fallen-Abomination-70B-R1-v4.1 benefits from the coherence and well rounded roleplay experience of TheDrummer/Fallen-Llama-3.3-R1-70B-v1. We've:
🔁 Re-integrated your favorite V1.2 scenarios (now with better kink distribution)
🧪 Direct-injected the Abomination dataset into the model's neural pathways
⚖️ Achieved perfect balance between "oh my" and "oh my"
Repository: localaiLicense: llama3.3
fallen-safeword-70b-r1-v4.1
ReadyArt/Fallen-Safeword-70B-R1-v4.1 isn't just a model - is the event horizon of depravity trained on TheDrummer/Fallen-Llama-3.3-R1-70B-v1. We've:
🔁 Re-integrated your favorite V1.2 scenarios (now with better kink distribution)
🧪 Direct-injected the Safeword dataset into the model's neural pathways
⚖️ Achieved perfect balance between "oh my" and "oh my"
Repository: localaiLicense: llama3.3
gemma-3-the-grand-horror-27b
The **Gemma-3-The-Grand-Horror-27B-GGUF** model is a **fine-tuned version** of Google's **Gemma 3 27B** language model, specifically optimized for **extreme horror-themed text generation**. It was trained using the **Unsloth framework** on a custom in-house dataset of horror content, resulting in a model that produces vivid, graphic, and psychologically intense narratives—featuring gore, madness, and disturbing imagery—often even when prompts don't explicitly request horror.
Key characteristics:
- **Base Model**: Gemma 3 27B (original by Google, not the quantized version)
- **Fine-tuned For**: High-intensity horror storytelling, long-form narrative generation, and immersive scene creation
- **Use Case**: Creative writing, horror RP, dark fiction, and experimental storytelling
- **Not Suitable For**: General use, children, sensitive audiences, or content requiring neutral/positive tone
- **Quantization**: Available in GGUF format (e.g., q3k, q4, etc.), making it accessible for local inference on consumer hardware
> ✅ **Note**: The model card you see is for a **quantized, fine-tuned derivative**, not the original. The true base model is **Gemma 3 27B**, available at: https://huggingface.co/google/gemma-3-27b
This model is not for all audiences — it generates content with a consistently dark, unsettling tone. Use responsibly.
Repository: localaiLicense: gemma