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
- Xet hash:
- 9369106c4375cfaa7ce6f5892d48b7ffdba56a5f92635fd114045cca2092a855
- Size of remote file:
- 27.9 MB
- SHA256:
- e0ca2e99eca05c8a688ec60100806dda193defc5839c985b321d9e8492efcb84
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