---
license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
base_model:
- mistralai/Mistral-Nemo-Instruct-2407
language:
- en
- ru
---

# Vikra-HCT-YeAM-Vikhr-NemoGemma-12B_plus_1B

HCT architecture release. YeAM (Yet Another Merge) implementation invariant.

## What it is

A large (12B-class) checkpoint produced via HCT-compatible merging with 1B Gemma.
Published in standard Hugging Face format (safetensors + sharded index) and intended to be convertible to GGUF.

## YeAM summary

YeAM performs a controlled merge in a real 4D geometric formulation with ray-intersection alignment in parameter space.
It also supports targeted knowledge injection (distillation-style) into a chosen model while remaining HF-compatible.

## Usage (Transformers)

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

m = "/path/to/Vikra-HCT-YeAM-Vikhr-NemoGemma-12B_plus_1B"

tok = AutoTokenizer.from_pretrained(m, use_fast=False)
model = AutoModelForCausalLM.from_pretrained(
    m,
    torch_dtype=torch.bfloat16,
    device_map="auto",
).eval()

inputs = tok("Привет!", return_tensors="pt").to(model.device)
out = model.generate(**inputs, max_new_tokens=256)
print(tok.decode(out[0], skip_special_tokens=True))
```

## GGUF (example)

```bash
python3 /path/to/llama.cpp/convert_hf_to_gguf.py /path/to/model --outtype bf16 --outfile model.bf16.gguf
/path/to/llama.cpp/build/bin/llama-quantize model.bf16.gguf model.Q6_K.gguf Q6_K
CUDA_VISIBLE_DEVICES=0,1 /path/to/llama.cpp/build/bin/llama-server -m model.Q6_K.gguf --n-gpu-layers 99 --split-mode layer --tensor-split 1,1