File size: 2,500 Bytes
2f8b1f1 4ea2f03 2f8b1f1 14b2798 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
🧪 Gemma-2B-DolphinR1-TestV2 (Experimental Fine-Tune) 🧪
This is an experimental fine-tune of Google's Gemma-2B using the Dolphin-R1 dataset.
The goal is to enhance reasoning and chain-of-thought capabilities while maintaining efficiency with LoRA (r=32) and 4-bit quantization.
🚨 Disclaimer: This model is very much a work in progress and is still being tested for performance, reliability, and generalization. Expect quirks, inconsistencies, and potential overfitting in responses.
Balkon mode confirmed lol. It's broken.
---
base_model: YorkieOH10/Gemma-2B-DolphinR1-Testv2
tags:
- llama-cpp
- gguf-my-repo
---
# YorkieOH10/Gemma-2B-DolphinR1-Testv2-Q8_0-GGUF
This model was converted to GGUF format from [`YorkieOH10/Gemma-2B-DolphinR1-Testv2`](https://huggingface.co/YorkieOH10/Gemma-2B-DolphinR1-Testv2) 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/YorkieOH10/Gemma-2B-DolphinR1-Testv2) for more details on the model.
## 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 YorkieOH10/Gemma-2B-DolphinR1-Testv2-Q8_0-GGUF --hf-file gemma-2b-dolphinr1-testv2-q8_0.gguf -p "The meaning to life and the universe is"
```
### Server:
```bash
llama-server --hf-repo YorkieOH10/Gemma-2B-DolphinR1-Testv2-Q8_0-GGUF --hf-file gemma-2b-dolphinr1-testv2-q8_0.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 YorkieOH10/Gemma-2B-DolphinR1-Testv2-Q8_0-GGUF --hf-file gemma-2b-dolphinr1-testv2-q8_0.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo YorkieOH10/Gemma-2B-DolphinR1-Testv2-Q8_0-GGUF --hf-file gemma-2b-dolphinr1-testv2-q8_0.gguf -c 2048
```
|