README.md

metadata

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:

• gchhablani/bert-base-cased-finetuned-sst2
• Wakaka/bert-finetuned-imdb

🧩 Configuration

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

!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"])