Text Classification
Transformers
Safetensors
mistral3
image-text-to-text
decision-model
schema-head
fp8
compressed-tensors
Instructions to use StandardThinking/StandardOne-8B-SH-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StandardThinking/StandardOne-8B-SH-FP8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="StandardThinking/StandardOne-8B-SH-FP8")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("StandardThinking/StandardOne-8B-SH-FP8") model = AutoModelForMultimodalLM.from_pretrained("StandardThinking/StandardOne-8B-SH-FP8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from StandardThinking/StandardOne-8B-SH-FP8: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/StandardThinking/StandardOne-8B-SH-FP8/resolve/main/tokenizer.json
- Command line
-
hf download hf://StandardThinking/StandardOne-8B-SH-FP8/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/StandardThinking/StandardOne-8B-SH-FP8/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 7614fa958ad3a9ad5b07c6fdbf9fb705e7af72e3cc05bb806f7b0436c387b862
- Size of remote file:
- 17.1 MB
- SHA256:
- d5f6046775b112f0e2d456ee9dba450684ab964fe5c4e231599bdc6773028135
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