File size: 1,556 Bytes
07d3af2 |
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 |
---
license: apache-2.0
tags:
- moe
- frankenmoe
- merge
- mergekit
- openchat/openchat-3.5-1210
- beowolx/CodeNinja-1.0-OpenChat-7B
base_model:
- openchat/openchat-3.5-1210
- beowolx/CodeNinja-1.0-OpenChat-7B
---
# my-llm
my-llm is a Mixture of Experts (MoE) made with the following models using [Mergekit](https://github.com/arcee-ai/mergekit):
* [openchat/openchat-3.5-1210](https://huggingface.co/openchat/openchat-3.5-1210)
* [beowolx/CodeNinja-1.0-OpenChat-7B](https://huggingface.co/beowolx/CodeNinja-1.0-OpenChat-7B)
## 🧩 Configuration
```yamlbase_model: mlabonne/Marcoro14-7B-slerp
experts:
- positive_prompts:
- chat
- tell me
source_model: openchat/openchat-3.5-1210
- positive_prompts:
- code
- python
- java
source_model: beowolx/CodeNinja-1.0-OpenChat-7B
experts_per_token: 2
gate_mode: hidden
```
## 💻 Usage
```python
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "mgv99/my-llm"
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"])
``` |