Instructions to use kunit17/BPLMerged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kunit17/BPLMerged with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="kunit17/BPLMerged")# Load model directly from transformers import AutoFeatureExtractor, AutoModelForTextToWaveform extractor = AutoFeatureExtractor.from_pretrained("kunit17/BPLMerged") model = AutoModelForTextToWaveform.from_pretrained("kunit17/BPLMerged") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio
How to use kunit17/BPLMerged with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for kunit17/BPLMerged to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for kunit17/BPLMerged to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for kunit17/BPLMerged to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="kunit17/BPLMerged", max_seq_length=2048, )
- Xet hash:
- 6d75eac6b9a247cbf5dec3b918efa3bae94cb0a40d1188cb5c49c70070ac2f23
- Size of remote file:
- 4.15 GB
- SHA256:
- 9c3f3ec8eb314b54c8db4070fbfd4265c4bf22917601ddc8daa698b170f96ace
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