---
library_name: transformers
pipeline_tag: text-generation
tags:
- 64k context
- reasoning
- thinking
- qwen3
- uncensored
- llama-cpp
- gguf-my-repo
base_model: DavidAU/Qwen3-8B-64k-Context-2X-Josiefied-Uncensored
---

# Triangle104/Qwen3-8B-64k-Context-2X-Josiefied-Uncensored-Q4_K_M-GGUF
This model was converted to GGUF format from [`DavidAU/Qwen3-8B-64k-Context-2X-Josiefied-Uncensored`](https://huggingface.co/DavidAU/Qwen3-8B-64k-Context-2X-Josiefied-Uncensored) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/DavidAU/Qwen3-8B-64k-Context-2X-Josiefied-Uncensored) for more details on the model.

---
This repo is for Goekdeniz-Guelmez's excellent "Josiefied-Qwen3-8B-abliterated-v1", modified from 32k (32768) context to 64 k (65536) context modified using YARN as per tech notes at Qwen repo.

ORG model repo for this fine tune:

[ https://huggingface.co/Goekdeniz-Guelmez/Josiefied-Qwen3-8B-abliterated-v1 ]

Max context on this version is : 64k (65536)

Suggest min context limit of : 8k to 16k for "thinking" / "output".

Use Jinja Template or CHATML template.

Please refer the QWEN model card for details, benchmarks, how to use, settings, turning reasoning on/off/ system roles etc etc :

[ https://huggingface.co/Qwen/Qwen3-8B ]

---
## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)

```bash
brew install llama.cpp

```
Invoke the llama.cpp server or the CLI.

### CLI:
```bash
llama-cli --hf-repo Triangle104/Qwen3-8B-64k-Context-2X-Josiefied-Uncensored-Q4_K_M-GGUF --hf-file qwen3-8b-64k-context-2x-josiefied-uncensored-q4_k_m.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Triangle104/Qwen3-8B-64k-Context-2X-Josiefied-Uncensored-Q4_K_M-GGUF --hf-file qwen3-8b-64k-context-2x-josiefied-uncensored-q4_k_m.gguf -c 2048
```

Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```

Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```

Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo Triangle104/Qwen3-8B-64k-Context-2X-Josiefied-Uncensored-Q4_K_M-GGUF --hf-file qwen3-8b-64k-context-2x-josiefied-uncensored-q4_k_m.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Triangle104/Qwen3-8B-64k-Context-2X-Josiefied-Uncensored-Q4_K_M-GGUF --hf-file qwen3-8b-64k-context-2x-josiefied-uncensored-q4_k_m.gguf -c 2048
```