Instructions to use bane5631/6923f14f-24b6-41e8-92ed-a104e57e5eda with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bane5631/6923f14f-24b6-41e8-92ed-a104e57e5eda with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Mistral-Nemo-Base-2407") model = PeftModel.from_pretrained(base_model, "bane5631/6923f14f-24b6-41e8-92ed-a104e57e5eda") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from bane5631/6923f14f-24b6-41e8-92ed-a104e57e5eda: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/bane5631/6923f14f-24b6-41e8-92ed-a104e57e5eda/resolve/main/tokenizer.json
- Command line
-
hf download hf://bane5631/6923f14f-24b6-41e8-92ed-a104e57e5eda/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/bane5631/6923f14f-24b6-41e8-92ed-a104e57e5eda/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 7b5b773d0adc4c15fe7b71c6eb88ac0a699522c5bc815a6368aa69e9470b8e44
- Size of remote file:
- 17.1 MB
- SHA256:
- b0240ce510f08e6c2041724e9043e33be9d251d1e4a4d94eb68cd47b954b61d2
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