Hugging Face's logo

liminerity
/
Memgpt-3x7b-MOE

Text Generation
Transformers
Safetensors
mixtral
Mixture of Experts
frankenmoe
Merge
mergekit
lazymergekit
starsnatched/MemGPT-DPO
starsnatched/MemGPT-3
starsnatched/MemGPT
conversational
text-generation-inference
Inference Endpoints
Model card Files Community
1
Memgpt-3x7b-MOE
File size: 2,547 Bytes 
0ac6b59
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
 
---
license: apache-2.0
tags:
- moe
- frankenmoe
- merge
- mergekit
- lazymergekit
- starsnatched/MemGPT-DPO
- starsnatched/MemGPT-3
- starsnatched/MemGPT
base_model:
- starsnatched/MemGPT-DPO
- starsnatched/MemGPT-3
- starsnatched/MemGPT
---

# Memgpt-3x7b-MOE

Memgpt-3x7b-MOE is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [starsnatched/MemGPT-DPO](https://huggingface.co/starsnatched/MemGPT-DPO)
* [starsnatched/MemGPT-3](https://huggingface.co/starsnatched/MemGPT-3)
* [starsnatched/MemGPT](https://huggingface.co/starsnatched/MemGPT)

## 🧩 Configuration

```yaml
base_model: liminerity/Memgpt-slerp-7b-5
gate_mode: hidden
dtype: bfloat16
experts:
  - source_model: starsnatched/MemGPT-DPO
    positive_prompts:
    - "versatile"
    - "helpful"
    - "factual"
    - "integrated"
    - "adaptive"
    - "comprehensive"
    - "balanced"
    negative_prompts:
    - "specialized"
    - "narrow"
    - "focused"
    - "limited"
    - "specific"

  - source_model: starsnatched/MemGPT-3
    positive_prompts:
    - "analytical"
    - "accurate"
    - "logical"
    - "knowledgeable"
    - "precise"
    - "calculate"
    - "compute"
    - "solve"
    - "work"
    - "python"
    - "javascript"
    - "programming"
    - "algorithm"
    - "tell me"
    - "assistant"
    negative_prompts:
    - "creative"
    - "abstract"
    - "imaginative"
    - "artistic"
    - "emotional"
    - "mistake"
    - "inaccurate"

  - source_model: starsnatched/MemGPT
    positive_prompts:
    - "instructive"
    - "clear"
    - "directive"
    - "helpful"
    - "informative"
    negative_prompts:
    - "exploratory"
    - "open-ended"
    - "narrative"
    - "speculative"
    - "artistic"
```

## 💻 Usage

```python
!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "liminerity/Memgpt-3x7b-MOE"

tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
)

messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```