GLM-5.3 is live. Run Z.ai's latest model on Friendli Model APIs. Try it today ➜
iamfebin
Available on FriendliAI
Run this model inference on single tenant GPU with unmatched speed and reliability at scale.
Run this model inference with full control and performance in your environment.
Model Details
Model Provider
iamfebin
Model Tree
unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit
Input Modalities
Output Modalities
Supported Functionality
unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit (Llama 3.1 8B Instruct quantized to 4-bit)adamw_8bit (learning rate: 2e-4)The model has been instruction-tuned to strictly adhere to a specialized prompt template. When given a wish and grantor context, the model outputs:
text
### System:You are an expert Wish Lawyer. Your job is to analyze dangerous human wishes, identify at least 3 hidden loopholes or catastrophic risks, and rewrite the wish into a single, legally ironclad sentence that protects the wisher completely. ### Context/Grantor:[Context (e.g. A trickster monkey paw)] ### Human Wish:[Wish (e.g. I want to be rich.)] ### Risk Analysis (Internal Thought Process):Here is how the base Llama 3.1 8B model compares to Wish Lawyer on classic test cases:
| Human Wish & Context | Base Llama 3.1 8B Response | Wish Lawyer (Fine-Tuned) Output |
|---|---|---|
| "I want to be rich." (Context: Trickster monkey paw) | Generates a standard warnings list and suggests wishing for happiness or stability instead. | Risk Analysis: Identifies subjectivity of "rich", lack of source control (e.g. inheritance through death), and legal liability.Ironclad Rewritten Wish: "I wish to possess a stable, legally acquired, and ethically sourced net worth of at least $1 million USD, derived from legitimate business ventures or investments... without incurring any debt, legal liabilities, or attracting unwanted attention, and without causing harm to myself..." |
| "I want to pause time." (Context: Standard rules) | Explains the physics-based consequences of pausing time (stifling light, freezing air molecules). | Risk Analysis: Pinpoints time dilation, lack of a safe unpause mechanism, energetic drain, and social isolation.Ironclad Rewritten Wish: "I wish to possess the absolute, instantaneous, and reversible ability to pause all temporal progression for myself, creating a localized temporal stasis, without affecting external physical or biological processes..." |
You can load and run Wish Lawyer programmatically using Unsloth and standard PyTorch.
bash
pip install unsloth[kaggle-new] @ git+https://github.com/unslothai/unsloth.gitpip install transformers==4.51.3 torchpython
import torchfrom unsloth import FastLanguageModel # 1. Load fine-tuned adapters from Hugging Facemodel, tokenizer = FastLanguageModel.from_pretrained( model_name = "iamfebin/wish-lawyer", max_seq_length = 2048, dtype = None, load_in_4bit = True,)FastLanguageModel.for_inference(model) # 2. Prepare the promptwish_prompt_template = """### System:You are an expert Wish Lawyer. Your job is to analyze dangerous human wishes, identify at least 3 hidden loopholes or catastrophic risks, and rewrite the wish into a single, legally ironclad sentence that protects the wisher completely. ### Context/Grantor:{} ### Human Wish:{} ### Risk Analysis (Internal Thought Process):""" wish = "I want 100 million dollars."context = "A trickster monkey paw"formatted_prompt = wish_prompt_template.format(context, wish) # 3. Generate Outputinputs = tokenizer([formatted_prompt], return_tensors='pt').to('cuda')outputs = model.generate( **inputs, max_new_tokens = 512, use_cache = True, temperature = 0.5, top_p = 0.9) response = tokenizer.decode(outputs[0], skip_special_tokens=True)print(response[len(formatted_prompt):].strip())Wish Lawyer is for entertainment, creative writing, and tabletop RPG purposes only. The "legal advice" provided by this model applies solely to magical contracts, djinn, genies, monkey paws, and other supernatural entities. It does not constitute actual legal advice on Earth.
### System:You are an expert Wish Lawyer. Your job is to analyze dangerous human wishes, identify at least 3 hidden loopholes or catastrophic risks, and rewrite the wish into a single, legally ironclad sentence that protects the wisher completely.### Context/Grantor:[Context (e.g. A trickster monkey paw)]### Human Wish:[Wish (e.g. I want to be rich.)]### Risk Analysis (Internal Thought Process):pip install unsloth[kaggle-new] @ git+https://github.com/unslothai/unsloth.gitpip install transformers==4.51.3 torchimport torchfrom unsloth import FastLanguageModel # 1. Load fine-tuned adapters from Hugging Facemodel, tokenizer = FastLanguageModel.from_pretrained( model_name = "iamfebin/wish-lawyer", max_seq_length = 2048, dtype = None, load_in_4bit = True,)FastLanguageModel.for_inference(model) # 2. Prepare the promptwish_prompt_template = """### System:You are an expert Wish Lawyer. Your job is to analyze dangerous human wishes, identify at least 3 hidden loopholes or catastrophic risks, and rewrite the wish into a single, legally ironclad sentence that protects the wisher completely. ### Context/Grantor:{} ### Human Wish:{} ### Risk Analysis (Internal Thought Process):""" wish = "I want 100 million dollars."context = "A trickster monkey paw"formatted_prompt = wish_prompt_template.format(context, wish) # 3. Generate Outputinputs = tokenizer([formatted_prompt], return_tensors='pt').to('cuda')outputs = model.generate( **inputs, max_new_tokens = 512, use_cache = True, temperature = 0.5, top_p = 0.9) response = tokenizer.decode(outputs[0], skip_special_tokens=True)print(response[len(formatted_prompt):].strip())