Audio-Text-to-Text
Transformers
Safetensors
English
Korean
fastslm
feature-extraction
audio
text-generation
custom_code
Eval Results
Instructions to use okestro-ai-lab/FastSLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use okestro-ai-lab/FastSLM with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("okestro-ai-lab/FastSLM", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download __init__.py from okestro-ai-lab/FastSLM: direct link, hf CLI and curl.
- Browser
- Download file 316 Bytes
-
https://huggingface.co/okestro-ai-lab/FastSLM/resolve/main/__init__.py
- Command line
-
hf download hf://okestro-ai-lab/FastSLM/__init__.py
-
curl -L -o __init__.py https://huggingface.co/okestro-ai-lab/FastSLM/resolve/main/__init__.py
316 Bytes
| from .configuration_fastslm import FastSLMConfig | |
| from .modeling_fastslm import FastSLMForConditionalGeneration # FastALMForCausalLM | |
| from transformers import AutoConfig, AutoModelForCausalLM | |
| AutoConfig.register("fastslm", FastSLMConfig) | |
| AutoModelForCausalLM.register(FastSLMConfig, FastSLMForConditionalGeneration) | |