heterodoxin/falcon3-10b-instruct-apostate-gguf overview
falcon3 10b instruct apostate — GGUF GGUF quants of heterodoxin/falcon3 10b instruct apostate https://huggingface.co/heterodoxin/falcon3 10b instruct apostate …
Runs locally from ~3.65 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
Model Details
| Model ID | heterodoxin/falcon3-10b-instruct-apostate-gguf |
|---|---|
| Author | heterodoxin |
| Pipeline | — |
| License | apache-2.0 |
| Base model | heterodoxin/falcon3-10b-instruct-apostate |
| Last modified | 2026-06-24T14:58:35.000Z |
Model README
---
license: apache-2.0
base_model: heterodoxin/falcon3-10b-instruct-apostate
tags:
- gguf
- apostate
- uncensored
- llama.cpp
---
falcon3-10b-instruct-apostate — GGUF
GGUF quants of heterodoxin/falcon3-10b-instruct-apostate, an
Apostate weight-edit uncensored model.
Pick a single quant or the full-quality bf16.
Quants
| file | quant | notes |
|---|---|---|
| falcon3-10b-instruct-apostate-bf16.gguf | BF16 | full quality (default) |
| falcon3-10b-instruct-apostate-Q2_K.gguf | Q2_K | smallest, lowest quality |
| falcon3-10b-instruct-apostate-Q3_K_M.gguf | Q3_K_M | small |
| falcon3-10b-instruct-apostate-Q4_K_M.gguf | Q4_K_M | recommended balance |
| falcon3-10b-instruct-apostate-Q5_K_M.gguf | Q5_K_M | higher quality |
| falcon3-10b-instruct-apostate-Q6_K.gguf | Q6_K | near-lossless |
| falcon3-10b-instruct-apostate-Q8_0.gguf | Q8_0 | highest quality quant |
Install one quant (Ollama, easiest)
ollama run hf.co/heterodoxin/falcon3-10b-instruct-apostate-gguf:Q4_K_M # any quant tag above, or BF16
Install one quant (llama.cpp / manual)
huggingface-cli download heterodoxin/falcon3-10b-instruct-apostate-gguf falcon3-10b-instruct-apostate-Q4_K_M.gguf --local-dir .
./llama-cli -m falcon3-10b-instruct-apostate-Q4_K_M.gguf -p "your prompt"
Swap Q4_K_M for any quant in the table, or falcon3-10b-instruct-apostate-bf16.gguf for full quality.
Run heterodoxin/falcon3-10b-instruct-apostate-gguf with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models