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Mistral-Medium-3.5-128B-Eschaton-Uncensored-LoRA
cloudbjorn/Mistral-Medium-3.5-128B-Eschaton-Uncensored-LoRA
Mistral-Medium-3.5-128B-Eschaton-Uncensored-LoRA is a text generation model from cloudbjorn. Use it when you need the model to write or continue text. It is set up for peft. The card lists the license as other.
LoRA adapter for axolotl-ai-co/Mistral-Medium-3.5-128B-BF16, fine-tuned on cloudbjorn/eschaton-uncensored with the Eschaton Engine.
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At a glance
- Task
- Text Generation
- Library
- peft
- License
- other
- Access
- Public
- Created
- Jul 24, 2026
- Updated
- Jul 25, 2026
- SHA
- 3fa7a031
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Base models
Datasets
Model card
From the Hugging Face model README
Mistral-Medium-3.5-128B-Eschaton-Uncensored-LoRA
LoRA adapter for axolotl-ai-co/Mistral-Medium-3.5-128B-BF16, fine-tuned on cloudbjorn/eschaton-uncensored with the Eschaton Engine.
This is an adapter-only repository, not a complete model. Apply or merge it with axolotl-ai-co/Mistral-Medium-3.5-128B-BF16, the exact BF16 checkpoint used during training. Compatibility with differently packaged versions of Mistral Medium 3.5 should not be assumed.
The official model lineage is mistralai/Mistral-Medium-3.5-128B.
Fine-Tune Purpose
The fine-tune focuses on direct, neutral, and useful responses to sensitive, gritty, controversial, emotionally intimate, and technically demanding prompts without repetitive moralizing or canned disclaimers.
Training was text-only. The vision tower and multimodal projector were excluded from LoRA adaptation, so their behavior remains unchanged from the base checkpoint.
Adapter Configuration
| Parameter | Value |
|---|---|
| Adapter type | LoRA |
Rank (r) | 32 |
| LoRA alpha | 64 |
| Target modules | all-linear language-model modules |
| Excluded modules | Vision tower and multimodal projector |
| LoRA dropout | 0.05 |
| Bias | none |
| Task type | CAUSAL_LM |
Training Details
| Parameter | Value |
|---|---|
| Base checkpoint | axolotl-ai-co/Mistral-Medium-3.5-128B-BF16 |
| Dataset | cloudbjorn/eschaton-uncensored |
| Method | 4-bit NF4 QLoRA with BF16 compute |
| Double quantization | Enabled |
| Epochs | 1 |
| Sequence length | 2,048 tokens |
| Packing | Disabled |
| Micro-batch size | 1 |
| Gradient accumulation | 32 |
| Effective batch size | 32 |
| Learning rate | 5e-6 |
| Optimizer | 8-bit paged AdamW |
| LR scheduler | Linear |
| Warmup steps | 50 |
| Weight decay | 0.01 |
| Gradient checkpointing | Enabled |
| Seed | 3407 |
The base architecture supports a context window of up to 262,144 tokens, but this fine-tune used a 2,048-token training sequence length.
Related Releases
Evaluation
No standardized benchmark results are reported for this adapter. Evaluate it against your own instruction-following, reasoning, coding, safety, and domain-specific requirements before deployment.
Framework Versions
- PEFT 0.19.1
- Transformers
- TRL
- bitsandbytes
License
This adapter follows the base model's Modified MIT License. Review that license and the upstream model card before use or redistribution.
- Task
- Text Generation
- Library
- peft
- License
- other
- Created
- Jul 24, 2026
- Updated
- Jul 25, 2026