Instructions to use cstr/llama3-8b-spaetzle-v33-mlx-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use cstr/llama3-8b-spaetzle-v33-mlx-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir llama3-8b-spaetzle-v33-mlx-4bit cstr/llama3-8b-spaetzle-v33-mlx-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
cstr/llama3-8b-spaetzle-v33-mlx-4bit
The Model cstr/llama3-8b-spaetzle-v33-mlx-4bit was converted to MLX format from cstr/llama3-8b-spaetzle-v33 using mlx-lm version 0.14.0.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("cstr/llama3-8b-spaetzle-v33-mlx-4bit")
response = generate(model, tokenizer, prompt="hello", verbose=True)
Provenance and EU AI Act Art. 53 note
- Base model: cstr/llama3-8b-spaetzle-v33 โ a mergekit merge published by the same maintainer as this repository. It is not a third-party upstream: the maintainer authored that model.
- What was done here: format conversion and/or quantisation of that base model only (MLX, INT4 precision). No further training, fine-tuning or merging was applied at this step.
- Licence:
llama3, inherited through the base model from the models it was built from. - Training data: none was used, added or selected at this conversion step. The base model's card lists the models it was built from; their training content is documented โ where it is documented at all โ by their respective providers.
- Provider status: under Regulation (EU) 2024/1689 this repository makes no provider claim for the conversion step. Any provider obligations attaching to the model itself โ including Art. 53(1)(c) copyright policy and Art. 53(1)(d) training-content summary โ attach at cstr/llama3-8b-spaetzle-v33, not here.
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Model size
1B params
Tensor type
F16
ยท
U32 ยท
Hardware compatibility
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