Text Generation
Transformers
Safetensors
mistral
mergekit
Merge
12b
chat
roleplay
creative-writing
DELLA-linear
conversational
text-generation-inference
Instructions to use redrix/GodSlayer-12B-ABYSS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use redrix/GodSlayer-12B-ABYSS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="redrix/GodSlayer-12B-ABYSS") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("redrix/GodSlayer-12B-ABYSS") model = AutoModelForCausalLM.from_pretrained("redrix/GodSlayer-12B-ABYSS") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use redrix/GodSlayer-12B-ABYSS with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "redrix/GodSlayer-12B-ABYSS" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "redrix/GodSlayer-12B-ABYSS", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/redrix/GodSlayer-12B-ABYSS
- SGLang
How to use redrix/GodSlayer-12B-ABYSS with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "redrix/GodSlayer-12B-ABYSS" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "redrix/GodSlayer-12B-ABYSS", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "redrix/GodSlayer-12B-ABYSS" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "redrix/GodSlayer-12B-ABYSS", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use redrix/GodSlayer-12B-ABYSS with Docker Model Runner:
docker model run hf.co/redrix/GodSlayer-12B-ABYSS
File size: 4,498 Bytes
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base_model:
- LatitudeGames/Wayfarer-12B
- ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.2
- PocketDoc/Dans-PersonalityEngine-V1.1.0-12b
- HumanLLMs/Human-Like-Mistral-Nemo-Instruct-2407
- TheDrummer/UnslopNemo-12B-v4
- romaingrx/red-teamer-mistral-nemo
- DavidAU/MN-GRAND-Gutenberg-Lyra4-Lyra-12B-DARKNESS
- rAIfle/Questionable-MN-bf16
- allura-org/MN-12b-RP-Ink
- IntervitensInc/Mistral-Nemo-Base-2407-chatml
library_name: transformers
tags:
- mergekit
- merge
- 12b
- chat
- roleplay
- creative-writing
- DELLA-linear
---
# GodSlayer-12B-ABYSS
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
The goal of this model is to remain fairly stable and coherent, while counteracting positivity-bias and improving realism and diverse responses.
Model #12
## Merge Details
### Merge Method
This model was merged using the NuSLERP merge method using [IntervitensInc/Mistral-Nemo-Base-2407-chatml](https://huggingface.co/IntervitensInc/Mistral-Nemo-Base-2407-chatml) as a base.
### Models Merged
The following models were included in the merge:
* [LatitudeGames/Wayfarer-12B](https://huggingface.co/LatitudeGames/Wayfarer-12B)
* [ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.2](https://huggingface.co/ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.2)
* [PocketDoc/Dans-PersonalityEngine-V1.1.0-12b](https://huggingface.co/PocketDoc/Dans-PersonalityEngine-V1.1.0-12b)
* [HumanLLMs/Human-Like-Mistral-Nemo-Instruct-2407](https://huggingface.co/HumanLLMs/Human-Like-Mistral-Nemo-Instruct-2407)
* [romaingrx/red-teamer-mistral-nemo](https://huggingface.co/romaingrx/red-teamer-mistral-nemo)
* [DavidAU/MN-GRAND-Gutenberg-Lyra4-Lyra-12B-DARKNESS](https://huggingface.co/DavidAU/MN-GRAND-Gutenberg-Lyra4-Lyra-12B-DARKNESS)
* [rAIfle/Questionable-MN-bf16](https://huggingface.co/rAIfle/Questionable-MN-bf16)
* [allura-org/MN-12b-RP-Ink](https://huggingface.co/allura-org/MN-12b-RP-Ink)
### Configuration
The following YAML configurations were used to produce this model:
```yaml
# P1:
models:
- model: PocketDoc/Dans-PersonalityEngine-V1.1.0-12b
parameters:
weight:
- filter: self_attn
value: 0.2
- filter: mlp
value: 0.2
- value: 0.2
density: 0.6
- model: ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.2
parameters:
weight:
- filter: self_attn
value: 0.15
- filter: mlp
value: 0.15
- value: 0.15
density: 0.55
- model: HumanLLMs/Human-Like-Mistral-Nemo-Instruct-2407
parameters:
weight:
- filter: self_attn
value: 0.1
- filter: mlp
value: 0.1
- value: 0.1
density: 0.5
- model: LatitudeGames/Wayfarer-12B
parameters:
weight:
- filter: self_attn
value: 0.25
- filter: mlp
value: 0.25
- value: 0.25
density: 0.65
base_model: TheDrummer/UnslopNemo-12B-v4
merge_method: della_linear
dtype: bfloat16
chat_template: "chatml"
tokenizer_source: union
parameters:
normalize: true
int8_mask: true
epsilon: 0.1
lambda: 1
```
```yaml
# P2:
models:
- model: rAIfle/Questionable-MN-bf16
parameters:
weight:
- filter: self_attn
value: 0.2
- filter: mlp
value: 0.2
- value: 0.2
density: 0.6
- model: DavidAU/MN-GRAND-Gutenberg-Lyra4-Lyra-12B-DARKNESS
parameters:
weight:
- filter: self_attn
value: 0.3
- filter: mlp
value: 0.3
- value: 0.3
density: 0.7
- model: allura-org/MN-12b-RP-Ink
parameters:
weight:
- filter: self_attn
value: 0.35
- filter: mlp
value: 0.35
- value: 0.35
density: 0.75
- model: romaingrx/red-teamer-mistral-nemo
parameters:
weight:
- filter: self_attn
value: 0.25
- filter: mlp
value: 0.25
- value: 0.25
density: 0.65
base_model: TheDrummer/UnslopNemo-12B-v4
merge_method: della_linear
dtype: bfloat16
chat_template: "chatml"
tokenizer_source: union
parameters:
normalize: true
int8_mask: true
epsilon: 0.1
lambda: 1
```
```yaml
# Final:
models:
- model: P1
parameters:
weight: 0.5
- model: P2
parameters:
weight: 0.5
base_model: IntervitensInc/Mistral-Nemo-Base-2407-chatml
merge_method: nuslerp
dtype: bfloat16
chat_template: "chatml"
tokenizer:
source: union
parameters:
normalize: true
int8_mask: true
```
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