---

base_model:

- deepreinforce-ai/Ornith-1.0-397B

base_model_relation: quantized

quantized_by: Alittlehammmer

license: mit

license_link: https://huggingface.co/deepreinforce-ai/Ornith-1.0-397B/blob/main/LICENSE

pipeline_tag: text-generation

library_name: gguf

tags:

- gguf

- quantized

- llama.cpp

- text-generation

- agentic-coding

---

Ornith-1.0-397B-GGUF

GGUF quantizations of deepreinforce-ai/Ornith-1.0-397B.

Converted to BF16 using convert_hf_to_gguf.py, then quantized using llama-quantize from llama.cpp.

Did not use an imatrix for any of these runs, something I want to explore for future model uploads.

Available quants

| Quant | Bits | Size | Notes |

| ------ | ----- | ------- | -------------------------------- |

| Q4_K_M | 4 | ~241 GB | Recommended |

| Q6_K | 6 | ~326 GB | Very high quality |

| BF16 | 16 | ~793 GB | Full precision, reference file |

Usage

Download the shards and run with llama.cpp. The split files are

loaded automatically when you point at the first shard:

llama-cli -m Ornith-1.0-397B-Q6_K/Ornith-1.0-397B-Q6_K-00001-of-00007.gguf -p "Hello"

llama.cpp handles the -00001-of-0000X split automatically, so you do not need to merge

the shards manually.

Original model

See the original model card

for details on capabilities, benchmarks, and license.