AbyssSynth-12B / README.md
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---
base_model:
- yamatazen/LorablatedStock-12B
- yamatazen/EtherealAurora-12B-v2
tags:
- merge
- mergekit
- lazymergekit
- yamatazen/LorablatedStock-12B
- yamatazen/EtherealAurora-12B-v2
---
<img src="./AbyssSynth.png" alt="Model Image"/>
# AbyssSynth-12B
<b><i>She holds the weight of a galaxy, a fragile infinity encased within a sphere of shimmering light.
<br> Darkness swirls beneath endless stars, vast and unfathomable, yet tempered by her calm grasp.
<br> Not a force of chaos, but of silent order, the abyss contained, a cosmos in delicate balance, where creation and oblivion meet.</i></b>
## πŸ”§ Recommended Sampling Settings:</b>
```yaml
Temperature: 0.75 to 1.25
Min P: 0.035
Context Length: Stable at 12k tokens, with possible support for extended contexts
```
## πŸ’¬ Prompt Format
Supports ChatML style messages. Example:
```yaml
<|im_start|>user
Your question here.
<|im_end|>
<|im_start|>assistant
```
AbyssSynth-12B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
## 🧩 Configuration
```yaml
merge_method: ties
base_model: yamatazen/LorablatedStock-12B
models:
- model: yamatazen/LorablatedStock-12B
parameters:
weight: 0.65
density: 1.0
- model: yamatazen/EtherealAurora-12B-v2
parameters:
weight: 0.35
density: 1.0
parameters:
normalize: false
int8_mask: false
dtype: bfloat16
layer_parameters:
- filter: "attn"
sources:
- model: yamatazen/LorablatedStock-12B
weight: 0.6
- model: yamatazen/EtherealAurora-12B-v2
weight: 0.4
- filter: "mlp"
sources:
- model: yamatazen/LorablatedStock-12B
weight: 0.55
- model: yamatazen/EtherealAurora-12B-v2
weight: 0.45
- filter: "embed_tokens"
sources:
- model: yamatazen/LorablatedStock-12B
weight: 1.0
- model: yamatazen/EtherealAurora-12B-v2
weight: 0.0
- filter: "layer_norm"
sources:
- model: yamatazen/LorablatedStock-12B
weight: 0.7
- model: yamatazen/EtherealAurora-12B-v2
weight: 0.3
```
## πŸ’» Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Marcjoni/AbyssSynth-12B-12B"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=1, top_k=0, top_p=1)
print(outputs[0]["generated_text"])
```