Instructions to use Ailiance-fr/apertus-math-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Ailiance-fr/apertus-math-lora with PEFT:
Task type is invalid.
- MLX
How to use Ailiance-fr/apertus-math-lora with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("Ailiance-fr/apertus-math-lora") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- MLX LM
How to use Ailiance-fr/apertus-math-lora with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "Ailiance-fr/apertus-math-lora" --prompt "Once upon a time"
File size: 268 Bytes
fbd04a7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"fine_tune_type": "lora",
"lora_parameters": {
"rank": 16,
"alpha": 32,
"dropout": 0.05,
"scale": 2.0
},
"num_layers": 16,
"lora_layers": [
"self_attn.q_proj",
"self_attn.k_proj",
"self_attn.v_proj",
"self_attn.o_proj"
]
} |