Instructions to use renalpha/glm47-flash-typo3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use renalpha/glm47-flash-typo3 with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("unsloth/GLM-4.7-Flash")
model = PeftModel.from_pretrained(base_model, "renalpha/glm47-flash-typo3")

Notebooks
Google Colab
Kaggle
Local Apps Settings

Unsloth Studio

How to use renalpha/glm47-flash-typo3 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 renalpha/glm47-flash-typo3 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 renalpha/glm47-flash-typo3 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for renalpha/glm47-flash-typo3 to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="renalpha/glm47-flash-typo3",
    max_seq_length=2048,
)

glm47-flash-typo3 / tokenizer.json

Commit History

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renalpha commited on Mar 27

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Upload tokenizer.json with huggingface_hub fd973ad verified

Upload tokenizer.json with huggingface_hub

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verified