Instructions to use AdityaPS/SpaceLLM_Single_Turn_QA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use AdityaPS/SpaceLLM_Single_Turn_QA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("openai/gpt-oss-20b") model = PeftModel.from_pretrained(base_model, "AdityaPS/SpaceLLM_Single_Turn_QA") - Transformers
How to use AdityaPS/SpaceLLM_Single_Turn_QA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="AdityaPS/SpaceLLM_Single_Turn_QA") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AdityaPS/SpaceLLM_Single_Turn_QA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "backend": "tokenizers", | |
| "bos_token": "<|startoftext|>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|return|>", | |
| "is_local": false, | |
| "local_files_only": false, | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<|endoftext|>", | |
| "tokenizer_class": "TokenizersBackend" | |
| } | |