README.md

---
license: mit
language:
- en
library_name: transformers
pipeline_tag: text-generation
---

**Model Card**

**Model Name:** BathSalt-1/daedalus-phi-3

**Model Type:** Large Language Model

**Description:** This model is a merge of the `Or4cl3-1/Daedalus_1` and `microsoft/Phi-3-mini-4k-instruct` models using the `LazyMergekit` library. It is designed for general-purpose natural language processing tasks.

**Metadata:**

* **License:** MIT License
* **Language:** English
* **Library:** Transformers
* **Base Model:** microsoft/Phi-3-mini-4k-instruct
* **Merge Method:** slerp
* **Layer Range:** [0, 32]
* **Parameters:**
	+ t:
		- filter: self_attn
		- value: [0, 0.5, 0.3, 0.7, 1]
		- filter: mlp
		- value: [1, 0.5, 0.7, 0.3, 0]
		- value: 0.5
	+ dtype: bfloat16

**Usage:**

* **Tokenizer:** AutoTokenizer
* **Model:** AutoModelForSeq2SeqLM
* **Pipeline:** text-generation
* **Device:** auto

**Example Code:**
```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "BathSalt-1/daedalus-phi-3"
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"])
```