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EmmanuelM1/roberta-movie-sentiment-multimodel
roberta-movie-sentiment-multimodel is a text classification model from EmmanuelM1. Use it when you need a label for a piece of text. It is set up for transformers.
roberta-movie-sentiment-multimodel is a merge of the following models using LazyMergekit: gchhablani/bert-base-cased-finetuned-sst2 Wakaka/bert-finetuned-imdb
Downloads · 30 days
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How the weights are stored.
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From the Hugging Face model README
roberta-movie-sentiment-multimodel is a merge of the following models using LazyMergekit:
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
!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"])