Instructions to use Elypha/Negative_LLAMA_70B-Q8-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Elypha/Negative_LLAMA_70B-Q8-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Negative_LLAMA_70B-Q8-mlx Elypha/Negative_LLAMA_70B-Q8-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Elypha/Negative_LLAMA_70B-Q8-mlx
The Model Elypha/Negative_LLAMA_70B-Q8-mlx was converted to MLX format from SicariusSicariiStuff/Negative_LLAMA_70B using mlx-lm version 0.21.5.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("Elypha/Negative_LLAMA_70B-Q8-mlx")
prompt="hello"
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
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Model size
71B params
Tensor type
U32
·
F16 ·
Hardware compatibility
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8-bit
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Model tree for Elypha/Negative_LLAMA_70B-Q8-mlx
Base model
meta-llama/Llama-3.1-70B Finetuned
meta-llama/Llama-3.3-70B-Instruct Finetuned
SicariusSicariiStuff/Negative_LLAMA_70B