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Question-answering
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Instructions to use logicssoftwaregmbh/logicsct-gemma2it27b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use logicssoftwaregmbh/logicsct-gemma2it27b 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-gemma2it27b")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("logicssoftwaregmbh/logicsct-gemma2it27b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download Modelfile from logicssoftwaregmbh/logicsct-gemma2it27b: direct link, hf CLI and curl.
- Browser
- Download file 359 Bytes
-
https://huggingface.co/logicssoftwaregmbh/logicsct-gemma2it27b/resolve/main/Modelfile
- Command line
-
hf download hf://logicssoftwaregmbh/logicsct-gemma2it27b/Modelfile
-
curl -L -o Modelfile https://huggingface.co/logicssoftwaregmbh/logicsct-gemma2it27b/resolve/main/Modelfile
359 Bytes
| # ollama modelfile auto-generated by llamafactory | |
| FROM . | |
| TEMPLATE """<bos>{{ if .System }}{{ .System }}{{ end }}{{ range .Messages }}{{ if eq .Role "user" }}<start_of_turn>user | |
| {{ .Content }}<end_of_turn> | |
| <start_of_turn>model | |
| {{ else if eq .Role "assistant" }}{{ .Content }}<end_of_turn> | |
| {{ end }}{{ end }}""" | |
| PARAMETER stop "<eos>" | |
| PARAMETER num_ctx 4096 | |