Gromenauer-7B / README.md
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metadata
license: apache-2.0
datasets:
  - fistro/gromenauer
language:
  - es
pipeline_tag: text-generation

Gromenauer-7B

gromenauer-7B logo

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)