license: apache-2.0
language:
- en
base_model: - mkurman/Qwen2.5-14B-DeepSeek-R1-1M
- huihui-ai/DeepSeek-R1-Distill-Qwen-14B-abliterated-v2
library_name: mlx
tags: - merge
- text-generation-inference
- code
An MLX bfloat16 FP16 model, 1M context length, uncensored.
Model Merge: DeepSeek-R1-Distill-Qwen-14B-abliterated-v2
Description:
This model is a tie merge of "huihui-ai/DeepSeek-R1-Distill-Qwen-14B-abliterated-v2" and "mkurman/Qwen2.5-14B-DeepSeek-R1-1M".
Recipes
Model Recipe:
- model: "huihui-ai/DeepSeek-R1-Distill-Qwen-14B-abliterated-v2"
parameters:
weight: 1
density: 1
merge_method: ties
base_model: "mkurman/Qwen2.5-14B-DeepSeek-R1-1M"
parameters:
density: 1
normalize: true
int8_mask: true
dtype: bfloat16
Merged Model:
The model was merged using the "ties" method.
Conversion to MLX Format
The model was converted to the MLX format with brainfloat16 precision using the following command:
mlx_lm.convert --hf-path FiditeNemini/Qwen2.5-14B-DeepSeek-R1-1M --mlx-path ./Unhinged-Qwen2.5-R1.bf16 --dtype bfloat16 -q --q-bits 16
Usage Example
You can use this model with the following code snippet:
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("FiditeNemini/Unhinged-Qwen2.5-R1.bf16")
tokenizer = AutoTokenizer.from_pretrained("FiditeNemini/Unhinged-Qwen2.5-R1.bf16")
Details
- Model type: CausalLM
- Context length: 4096 tokens
- License: Apache 2.0
Keywords
- DeepSeek-R1-Distill
- Qwen2.5
- Abliterated
- LLM
- 1M context