Instructions to use trl-internal-testing/tiny-LlamaForSequenceClassification-3.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trl-internal-testing/tiny-LlamaForSequenceClassification-3.2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="trl-internal-testing/tiny-LlamaForSequenceClassification-3.2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("trl-internal-testing/tiny-LlamaForSequenceClassification-3.2") model = AutoModelForSequenceClassification.from_pretrained("trl-internal-testing/tiny-LlamaForSequenceClassification-3.2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload config
Browse files- generation_config.json +12 -0
generation_config.json
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{
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"bos_token_id": 128000,
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"do_sample": true,
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"eos_token_id": [
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128001,
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128008,
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128009
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],
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"temperature": 0.6,
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"top_p": 0.9,
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"transformers_version": "4.57.3"
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}
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