sentiment analysis fine tuned model

Overview

Highlights

• Optimized for low-latency sentiment classification tasks
• Apache-2.0 license ensures flexible commercial deployment
• Reduced compute overhead compared to general LLMs
• Ideal for real-time feedback and monitoring pipelines

Usage

# Install Hugging Face transformers
pip install transformers torch

# Load model with transformers
from transformers import AutoModel, AutoTokenizer

model = AutoModel.from_pretrained("alsgyu/sentiment-analysis-fine-tuned-model")
tokenizer = AutoTokenizer.from_pretrained("alsgyu/sentiment-analysis-fine-tuned-model")

Hugging Face Download

We recommend downloading the model via the Hugging Face CLI or Hub SDK.

Guidance：Before downloading, install huggingface_hub with:

pip install -U huggingface_hub

CLI Download

Download the full repository

huggingface-cli download alsgyu/sentiment-analysis-fine-tuned-model

Download a single file to a local folder (e.g. config.json into ./dir)

huggingface-cli download alsgyu/sentiment-analysis-fine-tuned-model config.json --local-dir ./dir

See the official docs for more CLI options

SDK Download

# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('alsgyu/sentiment-analysis-fine-tuned-model')

Git Download

Make sure git-lfs is installed first

git lfs install
git clone https://huggingface.co/alsgyu/sentiment-analysis-fine-tuned-model

To skip LFS large-file downloads, use:

GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/alsgyu/sentiment-analysis-fine-tuned-model

Model files are hosted on the Hugging Face Hub — download directly via HF CLI / SDK / Git, not through this site.

PyTorch / Transformers Usage

Install Transformers

pip install -U transformers torch

Load the model and run inference

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained('alsgyu/sentiment-analysis-fine-tuned-model')
tokenizer = AutoTokenizer.from_pretrained('alsgyu/sentiment-analysis-fine-tuned-model')