Instructions to use samadpls/torchlight-phi4-mini-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use samadpls/torchlight-phi4-mini-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-4-mini-instruct") model = PeftModel.from_pretrained(base_model, "samadpls/torchlight-phi4-mini-lora") - MLX
How to use samadpls/torchlight-phi4-mini-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("samadpls/torchlight-phi4-mini-lora") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use samadpls/torchlight-phi4-mini-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 "samadpls/torchlight-phi4-mini-lora" --prompt "Once upon a time"
- Atomic Chat
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Add the LoRA adapter in PEFT and mlx-lm formats
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