Feature Extraction
Transformers
Safetensors
English
llama
text-generation-inference
unsloth
text-embeddings-inference
Instructions to use fqb/out_model_merged_16bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fqb/out_model_merged_16bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="fqb/out_model_merged_16bit")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("fqb/out_model_merged_16bit") model = AutoModel.from_pretrained("fqb/out_model_merged_16bit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from fqb/out_model_merged_16bit: direct link, hf CLI and curl.
- Browser
- Download file 18.4 MB
-
https://huggingface.co/fqb/out_model_merged_16bit/resolve/main/tokenizer.json
- Command line
-
hf download hf://fqb/out_model_merged_16bit/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/fqb/out_model_merged_16bit/resolve/main/tokenizer.json
18.4 MB
- Xet hash:
- a105822cdb179089dba5648b472fe92607cc99fb0590fca506faaa6d2836b972
- Size of remote file:
- 18.4 MB
- SHA256:
- ec54a55e3c6fc7318ea02cbd1a6eb1fb180bff1b58acbf068504a25f1b407b7b
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