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---
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"])
``` |