Qwen3.5 0.8 Cyber GGUF
A compact Qwen3.5 0.8B repository with a practical GGUF quantization ladder for local inference.
Fonte do modelo
- Tipo
- Text model
- Tamanho do arquivo
- 198 MB
- Modelo base
- Qwen/Qwen3.5-0.8B
- Versão
- vBF16
- Atualizado
- 4 de out. de 2026
- Publicador
- @reaperdoesntknow
- Downloads
- 8,7 mil
- Fonte
- Hugging Face
Descrição da fonte
Qwen3.5-0.8B Cyber — GGUF
A compact Qwen3.5 0.8B repository with a practical GGUF quantization ladder for local inference.
This card describes what is present in the repository. The public files do not document the fine-tuning dataset or provide evaluation results, so the Cyber label should be read as the repository variant name—not as a verified capability claim.
Repository contents
| Variant | Approximate size | Practical use |
|---|---|---|
BF16 | 1.52 GB | Highest-fidelity reference build |
Q8_0 | 812 MB | High-quality local inference |
Q6_K | 630 MB | Smaller high-quality option |
Q4_K_M | 529 MB | Recommended size/quality starting point |
Q2_K_L | 484 MB | Minimum footprint; expect greater quality loss |
BF16-mmproj | 207 MB | Multimodal projector artifact; see caveat below |
Run locally
With a recent llama.cpp build:
llama-cli \
-hf reaperdoesntknow/Qwen3.5-0.8-Cyber-GGUF:Q4_K_M \
--jinja
With Ollama:
ollama run hf.co/reaperdoesntknow/Qwen3.5-0.8-Cyber-GGUF:Q4_K_M
Multimodal note
The repository includes a BF16 mmproj file and its configuration includes vision components. That establishes that a projector artifact is present; it does not establish that the end-to-end multimodal path was validated for this release. Verify image input locally before depending on it.
Intended use
- Local experimentation with a small Qwen3.5 model.
- CPU- and memory-constrained prototyping.
- Reproducible comparison of quantization levels.
Do not treat the model as an authoritative source for security, legal, medical, or operational decisions.
Evaluation status and limitations
- No benchmark results or comparison baselines are published in this repository.
- The fine-tuning dataset and training recipe are not documented in the public files reviewed for this card.
- Quantization reduces memory use and can change output quality.
- Model outputs may be incorrect, incomplete, biased, or unsafe.
- The multimodal path requires independent verification.
Lineage and license
- Base model: Qwen/Qwen3.5-0.8B
- Format: GGUF
- Conversion tooling recorded by the repository: Unsloth / llama.cpp
- License: Apache-2.0
Part of the CIx cybersecurity model collection.
Fontes
1 fonte
Fontes
1 fonteVerificado 4 de out.
Artefatos de modelo
1 artefato
Artefatos de modelo
1 artefatoQwen_Qwen3.5-0.8B__project-qwen_1782801151.BF16-mmproj.gguf
gguf · BF16 · 198 MB · SHA-256 b2d347d00a09…43b4 · Hugging Face
BaixarTrechos de fonte
3 trechos
Trechos de fonte
3 trechos--- license: apache-2.0 base_model: - Qwen/Qwen3.5-0.8B pipeline_tag: text-generation library_name: gguf tags: - gguf - llama.cpp - unsloth - qwen3_5 - edge - quantized - conversational - convergent-intelligence --- # Qwen3.5-0.8B Cyber — GGUF A compact Qwen3.5 0.8B repository with a practical GGUF quantization ladder for local inference. This card describes what is present in the repository. The public files do not document the fine-tuning dataset or provide evaluation results, so the `Cyber` label should be read as the repository variant name—not as a verified capability claim. ## Repository contents | Variant | Approximate size | Practical use | |---|---:|---| | `BF16` | 1.52 GB | Highest-fidelity reference build | | `Q8_0` | 812 MB | High-quality local inference | | `Q6_K` | 630 MB | Smaller high-quality option | | `Q4_K_M` | 529 MB | Recommended size/quality starting point | | `Q2_K_L` | 484 MB | Minimum footprint; expect greater quality loss | | `BF16-mmproj` | 207 MB | Multimodal projector artifact; see caveat below | ## Run locally With a recent `llama.cpp` build: ```bash llama-cli \ -hf reaperdoesntknow/Qwen3.5-0.8-Cyber-GGUF:Q4_K_M \ --jinja ``` With Ollama: ```bash ollama run hf.co/reaperdoesntknow/Qwen3.5-0.8-Cyber-GGUF:Q4_K_M ``` ## Multimodal note The repository includes a BF16 `mmproj` file and its configuration includes vision components. That establishes that a projector artifact is present; it does not establish that the end-to-end multimodal path was validated for this release. Verify image input locally before depending on it. ## Intended use - Local experimentation with a small Qwen3.5 model. - CPU- and memory-constrained prototyping. - Reproducible comparison of quantization levels. Do not treat the model as an authoritative source for security, legal, medical, or operational decisions. ## Evaluation status and limitations - No benchmark results or comparison baselines are published in this repository. - The fine-tuning dataset and training recipe are not documented in the public files reviewed for this card. - Quantization reduces memory use and can change output quality. - Model outputs may be incorrect, incomplete, biased, or unsafe. - The multimodal path requires independent verification. ## Lineage and license - Base model: [Qwen/Qwen3.5-0.8B](https://huggingface.co/Qwen/Qwen3.5-0.8B) - Format: GGUF - Conver...
--- tags: - gguf - llama.cpp - unsloth - vision-language-model --- # Qwen3.5-0.8-Cyber-GGUF : GGUF This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth). **Example usage**: - For text only LLMs: `llama-cli -hf reaperdoesntknow/Qwen3.5-0.8-Cyber-GGUF --jinja` - For multimodal models: `llama-mtmd-cli -hf reaperdoesntknow/Qwen3.5-0.8-Cyber-GGUF --jinja` ## Available Model files: - `Qwen_Qwen3.5-0.8B__project-qwen_1782801151.Q2_K_L.gguf` - `Qwen_Qwen3.5-0.8B__project-qwen_1782801151.BF16-mmproj.gguf` This was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) <!-- cix-keeper-ts:2026-07-17T13:17:05Z -->
--- tags: - gguf - llama.cpp - unsloth - vision-language-model --- # Qwen3.5-0.8-Cyber-GGUF : GGUF This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth). **Example usage**: - For text only LLMs: `llama-cli -hf reaperdoesntknow/Qwen3.5-0.8-Cyber-GGUF --jinja` - For multimodal models: `llama-mtmd-cli -hf reaperdoesntknow/Qwen3.5-0.8-Cyber-GGUF --jinja` ## Available Model files: - `Qwen_Qwen3.5-0.8B__project-qwen_1782801151.Q2_K_L.gguf` - `Qwen_Qwen3.5-0.8B__project-qwen_1782801151.BF16-mmproj.gguf` This was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) <!-- cix-keeper-ts:2026-07-11T13:16:19Z -->
