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---
language:
- en
license: other
library_name: transformers
tags:
- mergekit
- merge
- llama-cpp
- gguf-my-repo
base_model: Nohobby/MS-Schisandra-22B-v0.3
---
# Triangle104/MS-Schisandra-22B-v0.3-Q4_K_M-GGUF
This model was converted to GGUF format from [`Nohobby/MS-Schisandra-22B-v0.3`](https://huggingface.co/Nohobby/MS-Schisandra-22B-v0.3) 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/Nohobby/MS-Schisandra-22B-v0.3) for more details on the model.
Merge Details
-
Merging steps
Karasik-v0.3
models:
- model: Mistral-Small-22B-ArliAI-RPMax-v1.1
parameters:
weight: [0.2, 0.3, 0.2, 0.3, 0.2]
density: [0.45, 0.55, 0.45, 0.55, 0.45]
- model: Mistral-Small-NovusKyver
parameters:
weight: [0.01768, -0.01675, 0.01285, -0.01696, 0.01421]
density: [0.6, 0.4, 0.5, 0.4, 0.6]
- model: MiS-Firefly-v0.2-22B
parameters:
weight: [0.208, 0.139, 0.139, 0.139, 0.208]
density: [0.7]
- model: magnum-v4-22b
parameters:
weight: [0.33]
density: [0.45, 0.55, 0.45, 0.55, 0.45]
merge_method: della_linear
base_model: Mistral-Small-22B-ArliAI-RPMax-v1.1
parameters:
epsilon: 0.05
lambda: 1.05
int8_mask: true
rescale: true
normalize: false
dtype: bfloat16
tokenizer_source: base
SchisandraVA3
(Config taken from here)
merge_method: della_linear
dtype: bfloat16
parameters:
normalize: true
int8_mask: true
tokenizer_source: base
base_model: Cydonia-22B-v1.3
models:
- model: Karasik03
parameters:
density: 0.55
weight: 1
- model: Pantheon-RP-Pure-1.6.2-22b-Small
parameters:
density: 0.55
weight: 1
- model: ChatWaifu_v2.0_22B
parameters:
density: 0.55
weight: 1
- model: MS-Meadowlark-Alt-22B
parameters:
density: 0.55
weight: 1
- model: SorcererLM-22B
parameters:
density: 0.55
weight: 1
Schisandra-v0.3
dtype: bfloat16
tokenizer_source: base
merge_method: della_linear
parameters:
density: 0.5
base_model: SchisandraVA3
models:
- model: unsloth/Mistral-Small-Instruct-2409
parameters:
weight:
- filter: v_proj
value: [0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0]
- filter: o_proj
value: [1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1]
- filter: up_proj
value: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
- filter: gate_proj
value: [0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0]
- filter: down_proj
value: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
- value: 0
- model: SchisandraVA3
parameters:
weight:
- filter: v_proj
value: [1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1]
- filter: o_proj
value: [0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0]
- filter: up_proj
value: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
- filter: gate_proj
value: [1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1]
- filter: down_proj
value: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
- value: 1
---
## 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/MS-Schisandra-22B-v0.3-Q4_K_M-GGUF --hf-file ms-schisandra-22b-v0.3-q4_k_m.gguf -p "The meaning to life and the universe is"
```
### Server:
```bash
llama-server --hf-repo Triangle104/MS-Schisandra-22B-v0.3-Q4_K_M-GGUF --hf-file ms-schisandra-22b-v0.3-q4_k_m.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/MS-Schisandra-22B-v0.3-Q4_K_M-GGUF --hf-file ms-schisandra-22b-v0.3-q4_k_m.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo Triangle104/MS-Schisandra-22B-v0.3-Q4_K_M-GGUF --hf-file ms-schisandra-22b-v0.3-q4_k_m.gguf -c 2048
```
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