Instructions to use rellabear/exp2_llama3.1_8b_context_ep3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rellabear/exp2_llama3.1_8b_context_ep3 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rellabear/exp2_llama3.1_8b_context_ep3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from rellabear/exp2_llama3.1_8b_context_ep3: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/rellabear/exp2_llama3.1_8b_context_ep3/resolve/main/tokenizer.json
- Command line
-
hf download hf://rellabear/exp2_llama3.1_8b_context_ep3/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/rellabear/exp2_llama3.1_8b_context_ep3/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- baf523d93da63bb496178791cc4968043b1992e374d25a6a648253066008e16b
- Size of remote file:
- 17.2 MB
- SHA256:
- 912e72517f7521f3273166a7879fe54c52b397f8c48ea80f8f1ed794beb24c09
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.