Question Answering
Transformers
Safetensors
PEFT
Spanish
llama
text-generation
resident-evil
qlora
llama-cpp
instruct
gaming
text-generation-inference
Instructions to use DavidCaraballoBulnes/ResidentEvil-QA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DavidCaraballoBulnes/ResidentEvil-QA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="DavidCaraballoBulnes/ResidentEvil-QA")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("DavidCaraballoBulnes/ResidentEvil-QA") model = AutoModelForCausalLM.from_pretrained("DavidCaraballoBulnes/ResidentEvil-QA", device_map="auto") - PEFT
How to use DavidCaraballoBulnes/ResidentEvil-QA with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 167779b3b66f0a961569b2cc273e0243d2f809b248f3e4ac9194004b5a77f373
- Size of remote file:
- 15.5 GB
- SHA256:
- ca084a188b4cb9b7a58296e9697ebaf37e781778325e56a44a63ae6fc4f6c346
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.