FineLlama-3.2-3B-Instruct-ead-openvino

This model was converted to OpenVINO from Geraldine/FineLlama-3.2-3B-Instruct-ead using optimum-intel via the export space.

Model Description

• Original Model: Geraldine/FineLlama-3.2-3B-Instruct-ead
• Framework: OpenVINO
• Task: Text Generation, EAD tag generation
• Language: English
• License: llama3.2

Features

• Optimized for Intel hardware using OpenVINO
• Supports text generation inference
• Maintains original model capabilities for EAD tag generation
• Integration with PyTorch

Installation

First make sure you have optimum-intel installed:

pip install optimum[openvino]

To load your model you can do as follows:

from optimum.intel import OVModelForCausalLM

model_id = "Geraldine/FineLlama-3.2-3B-Instruct-ead-openvino"
model = OVModelForCausalLM.from_pretrained(model_id)

Technical Specifications

Supported Features

• Text Generation
• Transformers integration
• PyTorch compatibility
• OpenVINO export
• Inference Endpoints
• Conversational capabilities

Model Architecture

• Base: meta-llama/Llama-3.2-3B-Instruct
• Fine-tuned: Geraldine/FineLlama-3.2-3B-Instruct-ead
• Final conversion: OpenVINO optimization

Usage Examples

from optimum.intel import OVModelForCausalLM
from transformers import AutoTokenizer

# Load model and tokenizer
model_id = "Geraldine/FineLlama-3.2-3B-Instruct-ead-openvino"
model = OVModelForCausalLM.from_pretrained(model_id)
tokenizer = AutoTokenizer.from_pretrained(model_id)

# Generate text
def generate_ead(prompt):
    inputs = tokenizer(prompt, return_tensors="pt")
    outputs = model.generate(**inputs)
    return tokenizer.decode(outputs[0])