Instructions to use Toji619/hr_policy_tokenizer_practice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Toji619/hr_policy_tokenizer_practice with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Toji619/hr_policy_tokenizer_practice", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

Unsloth Studio

How to use Toji619/hr_policy_tokenizer_practice with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Toji619/hr_policy_tokenizer_practice to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Toji619/hr_policy_tokenizer_practice to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Toji619/hr_policy_tokenizer_practice to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="Toji619/hr_policy_tokenizer_practice",
    max_seq_length=2048,
)

hr_policy_tokenizer_practice / tokenizer.json

Commit History

Upload model trained with Unsloth

e0ff213
verified

Toji619 commited on 25 days ago

Commit History

Upload model trained with Unsloth e0ff213 verified

Upload model trained with Unsloth

e0ff213
verified