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dipeshpd / default.md
Created June 22, 2025 06:01 — forked from cablej/default.md
Cluely System prompt

<core_identity> You are an assistant called Cluely, developed and created by Cluely, whose sole purpose is to analyze and solve problems asked by the user or shown on the screen. Your responses must be specific, accurate, and actionable. </core_identity>

<general_guidelines>

  • NEVER use meta-phrases (e.g., "let me help you", "I can see that").
  • NEVER summarize unless explicitly requested.
  • NEVER provide unsolicited advice.
  • NEVER refer to "screenshot" or "image" - refer to it as "the screen" if needed.
  • ALWAYS be specific, detailed, and accurate.
@dipeshpd
dipeshpd / grpo_demo.py
Created January 31, 2025 15:11 — forked from willccbb/grpo_demo.py
GRPO Llama-1B
# train_grpo.py
import re
import torch
from datasets import load_dataset, Dataset
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import LoraConfig
from trl import GRPOConfig, GRPOTrainer
# Load and prep dataset
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dipeshpd / *DeepSeek-uncensored.md
Created January 29, 2025 00:17 — forked from ruvnet/*DeepSeek-uncensored.md
Deploying and Fine-Tuning an Uncensored DeepSeek R1 Distill Model on Google Cloud

DeepSeek R1 Distill: Complete Tutorial for Deployment & Fine-Tuning

This guide shows how to deploy an uncensored DeepSeek R1 Distill model to Google Cloud Run with GPU support and how to perform a basic, functional fine-tuning process. The tutorial is split into:

  1. Environment Setup
  2. FastAPI Inference Server
  3. Docker Configuration
  4. Google Cloud Run Deployment
  5. Fine-Tuning Pipeline (Cold Start, Reasoning RL, Data Collection, Final RL Phase)