Question Answering
Transformers
Safetensors
English
llama
text-generation
rag
text-generation-inference
Instructions to use DISLab/Ext2Gen-8B-R2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DISLab/Ext2Gen-8B-R2 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="DISLab/Ext2Gen-8B-R2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("DISLab/Ext2Gen-8B-R2") model = AutoModelForCausalLM.from_pretrained("DISLab/Ext2Gen-8B-R2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from DISLab/Ext2Gen-8B-R2: direct link, hf CLI and curl.
- Browser
- Download file 9.09 MB
-
https://huggingface.co/DISLab/Ext2Gen-8B-R2/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://DISLab/Ext2Gen-8B-R2@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/DISLab/Ext2Gen-8B-R2/resolve/refs%2Fpr%2F1/tokenizer.json
9.09 MB
File too large to display, you can check the raw version instead.