Downloads · 30 days
130
9% of all-time downloads
Ttimms/Ornith-1.5-35B-A3B-REAP-50-bf16
Ornith-1.5-35B-A3B-REAP-50-bf16 is a text generation model from Ttimms. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
The 50%-REAP-pruned Ornith-1.5-35B-A3B in bf16 — the source checkpoint behind the NVFP4 and GGUF releases. Provided so others can produce their own quants (AWQ, EXL2, MLX, custom GGUF, …).
Downloads · 30 days
130
9% of all-time downloads
All-time downloads
1.5K
Public
Parameters
19B
38 GB on disk
Likes
0
Public
Click a slice to open those files.
.safetensors38 GB · 100%
From the Hugging Face model README
The 50%-REAP-pruned Ornith-1.5-35B-A3B in bf16 — the source checkpoint behind the NVFP4 and GGUF releases. Provided so others can produce their own quants (AWQ, EXL2, MLX, custom GGUF, …).
mtp_num_hidden_layers: 0), reload-verified with a real
forward pass.~19B parameters, qwen3_5_moe hybrid (Gated-DeltaNet + attention + MoE).Qwen3_5MoeForCausalLM
for text-only, or see the pipeline for the vision-strip step.Quality after NVFP4A16 quant: HumanEval+ 84.2%, MBPP+ 89.2% (greedy, instruct) — single greedy draws; see the NVFP4A16 card on run-to-run spread.
graph TD
Base["ornith-ai/Ornith-1.5-35B-A3B<br/>qwen3_5_moe - 256 experts - MTP head - ~65 GB bf16 - MIT"]
subgraph Build ["Build - RTX 5070 Ti, SM120"]
REAP["REAP expert prune 50% 256 -> 128"]
MTP["strip MTP head (1 -> 0, reload-verified)"]
StripV["strip vision tower (333 tensors)"]
Quant["GPTQ-NVFP4A16 quantize (~5.5 h, 12.47 GiB)"]
end
subgraph HF ["Published formats"]
A16["REAP-50-NVFP4A16 - 12.47 GiB (vLLM)"]
GGUF["REAP-50-GGUF (Q4_K_M / Q5_K_M / Q6_K / Q8_0)"]
BF16["REAP-50-bf16 (pruned source)"]
end
Bench["HumanEval+ 84.2% - MBPP+ 89.2% - SWE-bench Verified 44.0%"]
Base --> REAP --> MTP --> StripV --> Quant --> A16
StripV --> BF16
BF16 -. convert .-> GGUF
A16 --> Bench
Ttimms/Ornith-1.5-35B-A3B-REAP-50-NVFP4A16Ttimms/Ornith-1.5-35B-A3B-REAP-50-GGUFFull prune → strip → quant → serve → evaluate pipeline, with the bugs found and fixed along the way: https://github.com/t-timms/ornith-nvfp4
MIT (inherits from ornith-ai/Ornith-1.5-35B-A3B). Pruning via REAP
(github.com/CerebrasResearch/reap).