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---
tags:
- merge
- mergekit
- lazymergekit
- gchhablani/bert-base-cased-finetuned-sst2
- Wakaka/bert-finetuned-imdb
base_model:
- gchhablani/bert-base-cased-finetuned-sst2
- Wakaka/bert-finetuned-imdb
---
# roberta-movie-sentiment-multimodel
roberta-movie-sentiment-multimodel is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [gchhablani/bert-base-cased-finetuned-sst2](https://huggingface.co/gchhablani/bert-base-cased-finetuned-sst2)
* [Wakaka/bert-finetuned-imdb](https://huggingface.co/Wakaka/bert-finetuned-imdb)
## 🧩 Configuration
```yaml
models:
- model: gchhablani/bert-base-cased-finetuned-sst2
parameters:
weight: 0.5
- model: Wakaka/bert-finetuned-imdb
parameters:
weight: 0.5
merge_method: linear
dtype: float16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "EmmanuelM1/roberta-movie-sentiment-multimodel"
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"])
``` |