File size: 2,395 Bytes
8ddb3f3 41342c1 8ddb3f3 |
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 63 64 65 66 67 68 69 70 71 72 73 |
---
library_name: transformers
license: apache-2.0
base_model: nbeerbower/Mistral-Nemo-Prism-12B-v7
datasets:
- nbeerbower/Arkhaios-DPO
- nbeerbower/Purpura-DPO
tags:
- llama-cpp
- gguf-my-repo
---
# Triangle104/Mistral-Nemo-Prism-12B-v7-Q6_K-GGUF
This model was converted to GGUF format from [`nbeerbower/Mistral-Nemo-Prism-12B-v7`](https://huggingface.co/nbeerbower/Mistral-Nemo-Prism-12B-v7) 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/nbeerbower/Mistral-Nemo-Prism-12B-v7) for more details on the model.
---
Model details:
-
EXPERIMENTAL MODEL!!!
Mahou-1.5-mistral-nemo-12B-lorablated finetuned on Arkhaios-DPO and Purpura-DPO.
The goal was to reduce archaic language and purple prose in a completely uncensored model.
Method
ORPO tuned with 8x A40 for 10 epochs.
For this version, beta was increased to 2.
In conclusion, LoRA does not seem to be able to completely remove some of the language issues deeply embedded in 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 Triangle104/Mistral-Nemo-Prism-12B-v7-Q6_K-GGUF --hf-file mistral-nemo-prism-12b-v7-q6_k.gguf -p "The meaning to life and the universe is"
```
### Server:
```bash
llama-server --hf-repo Triangle104/Mistral-Nemo-Prism-12B-v7-Q6_K-GGUF --hf-file mistral-nemo-prism-12b-v7-q6_k.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/Mistral-Nemo-Prism-12B-v7-Q6_K-GGUF --hf-file mistral-nemo-prism-12b-v7-q6_k.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo Triangle104/Mistral-Nemo-Prism-12B-v7-Q6_K-GGUF --hf-file mistral-nemo-prism-12b-v7-q6_k.gguf -c 2048
```
|