---
license: apache-2.0
base_model: LiquidAI/LFM2.5-8B-A1B
tags:
  - lfm2
  - lfm2.5
  - moe
  - behzatindustries
  - text-generation
  - code
  - sft
  - dpo
  - gguf
  - ollama
language:
  - en
pipeline_tag: text-generation
---

# BehzatOne-8B-A1B v109

v109 GGUF conversion and Ollama release built from the latest fixed repo Modelfile.

## Version Lineage

- v105: ~109k-sample release with SFT plus anti-hallucination DPO.
- v106: agentic SFT plus DPO release.
- v107: merge release built from the v105 BF16 base plus the current v106 SFT and DPO adapters.
- v108: targeted agentic-format repair release on top of v107, focused on exact patch/file/JSON output and anti-schema-regurgitation.


## What changed

- Merged BF16 weights for this release.
- GGUF artifacts generated for both BF16 and Q4_K_M.
- Ollama Modelfiles included for BF16 and Q4 deployment.
- See the release summary above for the training focus of this version.

## Artifacts

- `/v109/` - merged BF16 HF model shards
- `gguf/BehzatOne-8B-A1B-v109.BF16.gguf` - BF16 GGUF
- `gguf/BehzatOne-8B-A1B-v109.Q4_K_M.gguf` - Q4_K_M GGUF
- `Modelfile.v109-bf16`
- `Modelfile.v109-q4`
- `Modelfile.v109-agent-q4`

## Status

Evaluation for this release should be run after upload. Previous release numbers are not reused here.

## Usage

For Transformers:

```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model = AutoModelForCausalLM.from_pretrained(
    "behzatindustries/BehzatOne-8B-A1B",
    subfolder="v109",
    torch_dtype=torch.bfloat16,
    trust_remote_code=True,
).cuda()
tokenizer = AutoTokenizer.from_pretrained(
    "behzatindustries/BehzatOne-8B-A1B",
    subfolder="v109",
    trust_remote_code=True,
)
```