File size: 1,499 Bytes
cbdac13 |
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 |
---
tags:
- merge
- mergekit
- lazymergekit
- Sao10K/Fimbulvetr-11B-v2
- NeverSleep/CausalLM-RP-34B
base_model:
- Sao10K/Fimbulvetr-11B-v2
- NeverSleep/CausalLM-RP-34B
---
# OxytocinEngineering-v2-45B-passthrough
OxytocinEngineering-v2-45B-passthrough is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Sao10K/Fimbulvetr-11B-v2](https://huggingface.co./Sao10K/Fimbulvetr-11B-v2)
* [NeverSleep/CausalLM-RP-34B](https://huggingface.co./NeverSleep/CausalLM-RP-34B)
## 🧩 Configuration
```yaml
slices:
- sources:
- model: Sao10K/Fimbulvetr-11B-v2
layer_range: [0, 48]
- sources:
- model: NeverSleep/CausalLM-RP-34B
layer_range: [0, 60]
merge_method: passthrough
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "weezywitasneezy/OxytocinEngineering-v2-45B-passthrough"
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=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
``` |