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# Cognitivess Model
## Usage
To use this model, first install the custom package:
```bash
pip install git+https://huggingface.co/CognitivessAI/cognitivess
```
Then, you can use the model like this:
```python
# pip install bitsandbytes accelerate
from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
import torch
# Set up quantization config
quantization_config = BitsAndBytesConfig(load_in_8bit=True)
# Load tokenizer and model
tokenizer = AutoTokenizer.from_pretrained("CognitivessAI/cognitivess")
model = AutoModelForCausalLM.from_pretrained(
"CognitivessAI/cognitivess",
quantization_config=quantization_config,
device_map="auto" # This will automatically distribute the model across available GPUs
)
# Prepare input
input_text = "Write me a poem about Machine Learning."
inputs = tokenizer(input_text, return_tensors="pt").to("cuda")
# Generate output
with torch.no_grad():
outputs = model.generate(**inputs, max_length=100)
# Decode and print the result
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```
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