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---
base_model: SzilviaB/SzilviaB-Daredevil-LongWriter-8B_abliterated
library_name: transformers
tags:
- mergekit
- merge
- llama-cpp
- gguf-my-repo
---
# Triangle104/SzilviaB-Daredevil-LongWriter-8B_abliterated-Q4_K_S-GGUF
This model was converted to GGUF format from [`SzilviaB/SzilviaB-Daredevil-LongWriter-8B_abliterated`](https://huggingface.co/SzilviaB/SzilviaB-Daredevil-LongWriter-8B_abliterated) 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/SzilviaB/SzilviaB-Daredevil-LongWriter-8B_abliterated) for more details on the model.
---
Model details:
-
This is a merge of pre-trained language models created using mergekit.
Merge Method
-
This model was merged using the SLERP merge method.
Models Merged
The following models were included in the merge:
mlabonne/NeuralDaredevil-8B-abliterated
THUDM/LongWriter-llama3.1-8b
Configuration
The following YAML configuration was used to produce this model:
models:
- model: mlabonne/NeuralDaredevil-8B-abliterated
- model: THUDM/LongWriter-llama3.1-8b
merge_method: slerp
base_model: mlabonne/NeuralDaredevil-8B-abliterated
dtype: bfloat16
parameters:
t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
---
## 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/SzilviaB-Daredevil-LongWriter-8B_abliterated-Q4_K_S-GGUF --hf-file szilviab-daredevil-longwriter-8b_abliterated-q4_k_s.gguf -p "The meaning to life and the universe is"
```
### Server:
```bash
llama-server --hf-repo Triangle104/SzilviaB-Daredevil-LongWriter-8B_abliterated-Q4_K_S-GGUF --hf-file szilviab-daredevil-longwriter-8b_abliterated-q4_k_s.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/SzilviaB-Daredevil-LongWriter-8B_abliterated-Q4_K_S-GGUF --hf-file szilviab-daredevil-longwriter-8b_abliterated-q4_k_s.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo Triangle104/SzilviaB-Daredevil-LongWriter-8B_abliterated-Q4_K_S-GGUF --hf-file szilviab-daredevil-longwriter-8b_abliterated-q4_k_s.gguf -c 2048
```
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