FineLlama-3.2-3B-Instruct-16bit-ead-openvino

This model was converted to OpenVINO from Geraldine/FineLlama-3.2-3B-Instruct-16bit-ead using optimum-intel via the export space.

Model Description

  • Original Model: Geraldine/FineLlama-3.2-3B-Instruct-16bit-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-16bit-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-16bit-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-16bit-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])
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