Text Generation
PEFT
Safetensors
materials
raman
spectroscopy
inverse-design
crystal-structure
lora
jarvis
Instructions to use knc6/ramangpt_dft_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use knc6/ramangpt_dft_model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/mistral-7b-bnb-4bit") model = PeftModel.from_pretrained(base_model, "knc6/ramangpt_dft_model") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from knc6/ramangpt_dft_model: direct link, hf CLI and curl.
- Browser
- Download file 3.51 MB
-
https://huggingface.co/knc6/ramangpt_dft_model/resolve/main/tokenizer.json
- Command line
-
hf download hf://knc6/ramangpt_dft_model/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/knc6/ramangpt_dft_model/resolve/main/tokenizer.json
3.51 MB
File too large to display, you can check the raw version instead.