ORP-0.8B GGUF
This repository provides GGUF quants for hamzah0asadullah/ORP-0.8B.
ORP (Old Role Play) 0.8B is a full-parameter SFT fine-tune of Qwen/Qwen3.5-0.8B on the PygmalionAI/PIPPA conversation archive. It is trained to produce concise, responsive dialogue in the style of classic conversational roleplay systems while maintaining coherence on compact hardware.
All GGUF files were converted from the original safetensors weights using llama.cpp at native BF16 precision, then quantized into standard k-quant variants.
Available Files and Quantizations
| File | Quant Type | Size | Description / Recommendation |
|---|---|---|---|
ORP-0.8B-BF16.gguf | BF16 | 1.41 GB | Full precision base conversion. Highest fidelity reference weights. |
ORP-0.8B-Q8_0.gguf | Q8_0 | 774 MB | Near-lossless 8-bit quantization. Recommended for best quality. |
ORP-0.8B-Q6_K.gguf | Q6_K | 601 MB | High quality retention with minimal degradation. Excellent balance. |
ORP-0.8B-Q5_K_M.gguf | Q5_K_M | 551 MB | Solid balance between memory usage and generation accuracy. |
ORP-0.8B-Q4_K_M.gguf | Q4_K_M | 505 MB | Fast, lightweight 4-bit quant. Recommended default for mobile and edge setups. |
ORP-0.8B-Q3_K_M.gguf | Q3_K_M | 445 MB | Compact footprint when memory headroom is strictly limited. |
ORP-0.8B-Q2_K.gguf | Q2_K | 403 MB | Maximum compression. Noticeable quality loss, intended for ultra-constrained environments. |
Requirements
ORP-0.8B uses the Qwen 3.5 architecture (Qwen3_5ForConditionalGeneration / qwen35 in llama.cpp), which incorporates hybrid linear attention and interleaved MRoPE.
Make sure your local llama.cpp build or downstream interface (LM Studio, Ollama, Jan) includes Qwen 3.5 support.
How to Use
1. With llama.cpp
Run the model from the terminal using llama-cli:
llama-cli -m ./ORP-0.8B-Q4_K_M.gguf \
-p "<|im_start|>system\nYou are a helpful roleplay assistant.<|im_end|>\n<|im_start|>user\nHey, how have you been?<|im_end|>\n<|im_start|>assistant\n" \
-n 256 \
-c 4096 \
--temp 0.7
To run a local OpenAI-compatible API server:
llama-server -m ./ORP-0.8B-Q4_K_M.gguf \
--host 127.0.0.1 \
--port 8080 \
-c 4096
2. With Ollama
Create a file named Modelfile in the same directory:
FROM ./ORP-0.8B-Q4_K_M.gguf
TEMPLATE """<|im_start|>system
{{ .System }}<|im_end|>
<|im_start|>user
{{ .Prompt }}<|im_end|>
<|im_start|>assistant
"""
PARAMETER stop "<|im_start|>"
PARAMETER stop "<|im_end|>"
PARAMETER stop "<|endoftext|>"
PARAMETER temperature 0.7
Then register and launch the model:
ollama create orp-0.8b -f Modelfile
ollama run orp-0.8b
3. With LM Studio
- Copy or move any
.gguffile from this folder into your LM Studio models directory. - Search for
ORP-0.8Bin your local models tab. - Load the model and select ChatML as the prompt format preset.
Model Details
- Original weights: hamzah0asadullah/ORP-0.8B
- Base model: Qwen/Qwen3.5-0.8B
- Training dataset: PygmalionAI/PIPPA
- Architecture: Qwen 3.5 (
Qwen3_5ForConditionalGeneration) - Parameters: ~0.85B
- Context window: Up to 262,144 tokens
- Vocabulary size: 248,320 tokens
- License: Apache 2.0
Attribution & Credits
Original model fine-tuning by hamzah0asadullah. Base model by Qwen. Training dataset by PygmalionAI.
GGUF conversions produced by Pink Pixel.
Made with 💖 by Pink Pixel