---

license: apache-2.0

base_model: Empero/Qwen3.8-9B

tags:

• qwen3.5
• function-calling
• tool-use
• qlora
• finetune
• gguf
• rocmfpx

pipeline_tag: text-generation

language:

• en

library_name: gguf

---

Qwen3.8-9B Hermes FC — Tooluse (GGUF)

ROCmFPX-quantized version of

JamieBradfield/qwen3.8-9b-hermes-fc-tooluse

(BF16 merge in the parent repo).

Quant details

| file | quant | size | notes |

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

| qwen3.8-9b-hf-fc-v28-175-Q4_0_ROCMFP4_FAST.gguf | Q4_0_ROCMFP4_FAST | 4.69 GB | ROCmFPX (AMD RDNA3 kernels); fast-path quant of the BF16 merge |

Convert/quantize: llama-rocmfpx fork, convert_hf_to_gguf.py --outtype bf16

→ llama-quantize Q4_0_ROCMFP4_FAST.

ROCmFPX quants target AMD ROCm inference (RX 7700 XT in the author's rig,

12 GB VRAM, served at 64k context with q8_0/turbo3 KV — the measured sweet

spot: ~5.5x decode speed vs 245k context). For portable use, convert from

the BF16 merge in the parent repo instead.

Addendum 2026-09-03 — evaluation-methodology correction

The evaluation claims on the original card for this repo came from a

synthetic harness that baked tool schemas into the system text and never

passed the OpenAI tools parameter. Through the native tools path (the

interface live Hermes uses), the base model — no fine-tuning — fires

tier-1 at 18/20 with zero tier-4 drift, and this model's tier-2

todo-first advantage shrinks to 8/10 vs the base's 3/10 (see the full

corrected table in the

parent repo card).

The fine-tune program is frozen as of 2026-09-03; the base model is the

author's runtime default.

Note on the MTP head

The quant preserves the 15-tensor MTP (multi-token prediction) head from

the base under the mtp.* tensor prefix (442 tensors total in this

GGUF), usable with --spec-type draft-mtp on supporting builds.