bertin-project / Gromenauer-7B

Gromenauer-7B

Overview

Gromenauer-7B is a Spanish language model designed to understand and generate high-quality Spanish text. Developed using the robust Mistral architecture, this model has been trained on an extensive literary corpus, ensuring it captures a wide range of linguistic nuances, styles, and contexts found in Spanish literature.

Model Details

• Model Type : Mistral
• Sequence Length : 8192
• Hidden Dimension : 4096
• Intermediate Dimension : 14336
• Number of Layers : 32
• Number of Attention Heads : 32
• Number of Key-Value Heads : 8
• Activation Function : SiLU
• Initializer Range : 0.02
• Layer Norm Epsilon : 1.0e-05
• Use Flash Attention : Yes
• Gradient Checkpointing : Enabled (Block Size: 5)
• Sliding Window Attention : 4096
• Use Bias : No

Training Details

• Tokenizer : mistralai/Mistral-7B-v0.1
• Batch Size : 512
• Learning Rate : 1e-5
• Optimizer : Adam with beta1=0.9, beta2=0.95, epsilon=1e-8
• Weight Decay : 0.1
• Warmup Steps : 200
• Learning Rate Schedule : Cosine
• Number of Training Steps : 7000

Usage

To load the model in your project, you can use the following code:

from transformers import AutoModel, AutoTokenizer

# Load the tokenizer
tokenizer = AutoTokenizer.from_pretrained("bertin-project/Gromenauer-7B")

# Load the model
model = AutoModel.from_pretrained("bertin-project/Gromenauer-7B")

# Example usage
text = "Introduce aquí tu texto en español."
inputs = tokenizer(text, return_tensors="pt")
outputs = model(**inputs)