---
tags:
- text-generation-inference
- text-generation
- Sentiment Analysis
license: apache-2.0
library_name: transformers
widget:
- messages:
- role: user
content: What is your name?
language:
- en
- ro
---
Accessible and portable generative AI solutions for developers and businesses.
***Description***
"Bella-2-8b" by Cognitivess is a text generation model tailored for empathic AI interactions, supporting both English and Romanian languages.
The model, built on the transformers architecture, features 8.03 billion parameters , well-suited for a variety of text generation tasks, including question answering, summarization, reasoning, dialogue, sentiment analysis.
It employs a floating-point 16 (BF16) tensor type for operations, facilitating speech-to-speech applications.
Licensed under Cognitivess AI, Bella-2-8b is available on the Hugging Face platform for wide accessibility.
### Intended use
Bella-2-8B is a multilingual chat model designed to support a variety of languages including English, Romanian, Spanish, French, German, and many more, intended for diverse language applications.
**Model Developer:** Cognitivess AI
**Model Dates:** Bella-2-8b was trained between May 2024 and June 2024.
**Data Freshness:** The pretraining data has a cutoff of June 2024. Training will continue beyond the current data cutoff date to incorporate new data as it becomes available.
### Model Architecture:
Bella-2-8B model architecture is Transformer-based and trained with a sequence length of 8192 tokens.
**Architecture Type:** Transformer (auto-regressive language model)
Try this model on [bella.cognitivess.com](https://bella.cognitivess.com/) now.
# Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
model_path = "CognitivessAI/bella-2-8b"
# Load the tokenizer and model, converting model to half precision
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(model_path).half().eval()
# Move the model to CUDA if available
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model.to(device)
# Prompt content: "hi"
messages = [
{"role": "user", "content": "Who are you?"}
]
input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
# Move input_ids to the same device as the model
input_ids = input_ids.to(device)
# Adjust the generate method to set max_new_tokens
output_ids = model.generate(input_ids, max_new_tokens=50)
response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
# Model response: "I'm Bella, an AI model developed by Cognitivess."
print(response)
```
**Contact:**
hello@cognitivess.com