Question Answering
Transformers
Safetensors
German
phi3
text-generation
Connect-Transport
Logics Software
German support chatbot
Deutscher KI Chatbot
Kundenservice Chatbot
Deutscher Chatbot
KI-Chatbots für Unternehmen
Chatbot for SMEs
Question-answering
QLoRA fine-tuning
LLM training
custom_code
text-generation-inference
Instructions to use logicssoftwaregmbh/logicsct-phi4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use logicssoftwaregmbh/logicsct-phi4 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="logicssoftwaregmbh/logicsct-phi4", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("logicssoftwaregmbh/logicsct-phi4", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("logicssoftwaregmbh/logicsct-phi4", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
training based on logicsct_train_prompts_20250208_113921.json (#1)
Verified signature- training based on logicsct_train_prompts_20250208_113921.json (576b866460cb425437137a8705ba04982c76236d)938f5b3 -
Update README.md
Verified signature8ed9715 -
Update README.md
Verified signature7c17d0b -
Update README.md
Verified signature856f5bf -
Update README.md
Verified signature3d9f9c0 -
initial commit
Verified signature6f4aec2