Feature Extraction
Transformers
Safetensors
English
custom_model
multi-modal
speech-language
custom_code
Eval Results (legacy)
Instructions to use skit-ai/speechllm-1.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use skit-ai/speechllm-1.5B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="skit-ai/speechllm-1.5B", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("skit-ai/speechllm-1.5B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 944681b1f18175817dbf65ed7298a1512de5a075c891d156df33db360c63d450
- Size of remote file:
- 1.89 MB
- SHA256:
- 76788dffd2fd7b5bc505ee48b9d03145b8cf634ae50ac42157fa2086815f3a08
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