Gromenauer-7B

Gromenauer-7B

<div align=center> <img alt="gromenauer-7B logo" src="https://huggingface.co/bertin-project/Gromenauer-7B/resolve/main/images/gromenauer.png" width="200px"> </div>

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)