TenZzz412/MiniCPM5-1B-Claude-Opus-Fable5-Thinking-GGUF
<p align="center"> <img src="assets/banner.png" alt="MiniCPM5-1B-Claude-Opus-Fable5-Thinking-GGUF" width="100%"/> </p>
MiniCPM5-1B-Claude-Opus-Fable5-Thinking-GGUF
π’ V2.0 is available β We have released an updated model with enhanced tool-calling capabilities. Welcome to try the new version: - Transformers: MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking - GGUF: MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking-GGUF
GGUF quantizations of [MiniCPM5-1B-Claude-Opus-Fable5-Thinking](https://huggingface.co/GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-Thinking) for llama.cpp, Ollama, LM Studio, jan, KoboldCpp, and other GGUF runtimes.
δΈζθ―΄ζ
This repository provides local-deployment builds of a 1B Thinking model fine-tuned on Fable 5 data atop openbmb/MiniCPM5-1B. The GGUF files embed MiniCPM5's native chat template for llama.cpp-compatible runtimes.
Transformers checkpoint: [MiniCPM5-1B-Claude-Opus-Fable5-Thinking](https://huggingface.co/GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-Thinking)
Files
Q8_0 is the recommended default quant for this 1B model.
Quick start
llama.cpp (llama-cli)
llama-cli \
-m MiniCPM5-1B-Claude-Opus-Fable5-Thinking-Q8_0.gguf \
-p "Write a Python function to merge two sorted lists." \
-n 512 \
--temp 0.9 --top-p 0.95 \
-c 8192The model supports up to 128K tokens (131,072) perconfig.json. Set-caccording to your available VRAM/RAM.
llama.cpp server
llama-server \
-m MiniCPM5-1B-Claude-Opus-Fable5-Thinking-Q8_0.gguf \
-c 8192 --port 8080LM Studio / jan / KoboldCpp
Load any .gguf file from this repository. The MiniCPM5 chat template is embedded in the GGUF metadata.
Sampling recommendations
Generation defaults are inherited from [MiniCPM5-1B](https://huggingface.co/openbmb/MiniCPM5-1B):
Capabilities
- Fable 5 fine-tune β post-trained on Fable 5 data
- Coding β code generation, debugging, and software-engineering workflows
- Instruction following β more reliable adherence to user prompts and task constraints
- Thinking mode β chain-of-thought reasoning; MiniCPM5 chat template baked into the GGUF
- Long context β up to 128K tokens (131,072 tokens per upstream
config.json)
Limitations
- Thinking outputs β the model may emit reasoning blocks before the final answer
- 1B scale β lightweight local deployment; not frontier-scale
- Runtime context β actual usable context depends on your GGUF runtime and hardware limits
Provenance & licensing
Apache-2.0, inherited from MiniCPM5-1B.
Acknowledgements
- Base model: OpenBMB / MiniCPM5-1B
- Transformers checkpoint: MiniCPM5-1B-Claude-Opus-Fable5-Thinking
- Quantization: llama.cpp
