RichardErkhov/bertin-project_-_Gromenauer-7B-gguf

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Gromenauer-7B - GGUF

• —Model creator: https://huggingface.co/bertin-project/
• —Original model: https://huggingface.co/bertin-project/Gromenauer-7B/

Original model description: --- license: apache-2.0 datasets:

• —fistro/gromenauer language:
• —es pipeline_tag: text-generation ---

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)