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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 from transformers import pipeline pipe = pipeline("question-answering", model="logicssoftwaregmbh/logicsct-gemma2it27b")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("logicssoftwaregmbh/logicsct-gemma2it27b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 359 Bytes
b78ba14 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | # 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
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