Instructions to use aequa-tech/flame-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aequa-tech/flame-it with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aequa-tech/flame-it")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aequa-tech/flame-it") model = AutoModelForSequenceClassification.from_pretrained("aequa-tech/flame-it", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download rng_state.pth from aequa-tech/flame-it: direct link, hf CLI and curl.
- Browser
- Download file 14.2 kB
-
https://huggingface.co/aequa-tech/flame-it/resolve/main/rng_state.pth
- Command line
-
hf download hf://aequa-tech/flame-it/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/aequa-tech/flame-it/resolve/main/rng_state.pth
14.2 kB
- Xet hash:
- 8324e4c153941f34c4bed3a15363c952ff0e4b1eba4fe703878df3023de5a35c
- Size of remote file:
- 14.2 kB
- SHA256:
- 561b915c2a290cbe2e257b0f79b055907d8a92ac1b6523a10ab63f76d6ae3fa0
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