Instructions to use barnybug/stack-llama-2-ggml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use barnybug/stack-llama-2-ggml with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("barnybug/stack-llama-2-ggml", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download stack-llama-2-7b.ggmlv3.q4_0.bin from barnybug/stack-llama-2-ggml: direct link, hf CLI and curl.
- Browser
- Download file 3.83 GB
-
https://huggingface.co/barnybug/stack-llama-2-ggml/resolve/main/stack-llama-2-7b.ggmlv3.q4_0.bin
- Command line
-
hf download hf://barnybug/stack-llama-2-ggml/stack-llama-2-7b.ggmlv3.q4_0.bin
-
curl -L -o stack-llama-2-7b.ggmlv3.q4_0.bin https://huggingface.co/barnybug/stack-llama-2-ggml/resolve/main/stack-llama-2-7b.ggmlv3.q4_0.bin
3.83 GB
- Xet hash:
- de6a63847b5dad098b61ec31ad7afdef9536c081e2c881c44703d7a7fbe9ea30
- Size of remote file:
- 3.83 GB
- SHA256:
- 1ea64febecdd21fc63e7b31c481ca0fb41d16c5be00c8ffc8831a926c81342da
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