gpt-oss-10.8b-specialized-all-pruned-moe-only-15-experts

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

# Check MPS availability and load model
device = "mps" if torch.backends.mps.is_available() else "cpu"

model = AutoModelForCausalLM.from_pretrained(
    "AmanPriyanshu/gpt-oss-10.8b-specialized-all-pruned-moe-only-15-experts", 
    torch_dtype=torch.float16,  # Better MPS compatibility
    device_map=device, 
    trust_remote_code=True,
    low_cpu_mem_usage=True
)
tokenizer = AutoTokenizer.from_pretrained("AmanPriyanshu/gpt-oss-10.8b-specialized-all-pruned-moe-only-15-experts")

# Generate with the model
messages = [
    {"role": "user", "content": "What is artificial intelligence and how does it work?"}
]

inputs = tokenizer.apply_chat_template(
    messages, 
    add_generation_prompt=True, 
    return_tensors="pt", 
    return_dict=True,
    reasoning_effort="medium"
)

# Move inputs to model device
inputs = {k: v.to(model.device) if isinstance(v, torch.Tensor) else v for k, v in inputs.items()}

# Use torch.no_grad for MPS stability
with torch.no_grad():
    outputs = model.generate(
        **inputs, 
        max_new_tokens=512,
        do_sample=True,
        temperature=0.1,
        top_p=0.9,
        pad_token_id=tokenizer.eos_token_id,
        eos_token_id=tokenizer.eos_token_id,
        use_cache=True
    )

# Decode only the generated part
input_length = inputs['input_ids'].shape[1]
response_tokens = outputs[0][input_length:]
response = tokenizer.decode(response_tokens, skip_special_tokens=True)
print(response)

device_map="auto"  # Will automatically use GPU if available
torch_dtype=torch.bfloat16  # or torch.float16

<|channel|>analysis<|message|>Need explain AI, definition, components, how it works.<|end|><|start|>assistant<|channel|>final<|message|>## 1. What is Artificial Intelligence?

Artificial Intelligence (AI) is a field of computer science that seeks to build systems capable of **intelligent behavior**—that is, the ability to learn, reason, and act in a way that mimises human cognition.  
In practice, AI systems are built from a combination of:

| Component | What it does | Typical technology |
|---|---|---|
| **Sensors / Input** | Gathers raw data (text, images, sound, etc.) | Cameras, microphones, text encoders |
| **Representation** | Turns raw data into a machine‑friendly format | Neural‑network layers, symbolic models, graphs |
| **Processing / Reasoning** | Manipulates the representation to produce insights | Algorithms, inference engines, pattern‑matching |
| **Learning** | Improves the system over time | Machine‑learning, reinforcement learning, deep‑learning |
| **Output / Action** | Communes or acts on the insight | Speech, text, images, robot motion |

The “intelligence” comes from the system’s ability to **learn from experience** (data) and **generalize** that learning to new situations.

---

## 2. How AI Works – A Step‑by‑Step Overview

Below is a simplified pipeline that most AI systems follow. The exact details vary by domain (e.g., language, vision, robotics), but the core ideas are the same.

### 1. **Data Acquisition**

- **Input**: Sensors or pre‑existing data (e.g., a sentence, a photo, a video clip).
- **Encoding**: Convert the raw signal into a digital format (e.g., bytes, pixels, tokens).

### 2. **Representation**

- **Modeling**: Build a structure that captures the essential features of the input.
  - *Symbolic models*: Grammar trees for language, logic gates for circuits.
  - *Statistical models*: Feature vectors, probability distributions.
  - *Neural models*: Layers of neurons that learn patterns.

### 3. **Processing / Reasoning**

- **Inference**: Apply rules or learned patterns to the representation.
  - *Rule‑based*: If‑then logic, Boolean networks.
  - *Statistical*: Bayesian inference, expectation maximization.
  - *Neural*: Conference of layers, attention mechanisms.

### 4. **Learning**

<|channel|>analysis<|message|>Need simple explanation.<|end|><|start|>assistant<|channel|>final<|message|>**Einstein’s Theory of Relativity – in plain words**

---

### 1. What the theory is about

Einstein’s work is split into two main ideas:

| **Part** | **What it says** | **Why it matters** |
|---|---|---|
| **Classical (First) Relativity** | The speed of a moving object is measured relative to a reference point. | It explains why a car looks faster when you’re on a moving train. |
| **Quantum (Second) Relativity** | Space and time are not fixed; they can change depending on how fast something moves, especially near very fast (near‑light‑speed) objects. | It shows that the universe is a “soup” of particles that can behave in ways we can’t see with normal eyes. |

---

### 2. The “Classical” part – *Relative speed*

- **Speed is relative**: If you’re on a car that’s moving at 100 km/h, a car that’s moving at 200 km/h looks like it’s going 100 km/h faster.  
- **No absolute speed**: There is no single “speed” that exists everywhere; it always depends on who’s point of reference.

---

### 3. The “Quantum” part – *Space, time, and light*

- **Particles can be “fuzzy”**: In the quantum world, particles can be in many places at the same time.  
- **Light is a particle**: Light isn’t a single, fixed thing; it’s a stream of particles that can move at the speed of light (≈ 300 000 km/s).  
- **Time can bend**: Near a very fast object (like a super‑fast spaceship or a black hole), the flow of time can change. Things that happen in the future can appear to happen sooner or later.

---

### 4. How it changed our view

- **Gravity is not a force**: Einstein showed that gravity is a *field* that pulls objects because of the way space itself is arranged.  
- **The universe is a “wave”**: The universe is full of waves (light, sound, etc.) that carry information.  
- **New physics**: The theory opened the way to quantum mechanics, explaining why atoms behave in ways that classical physics can’t predict.

---

### 5. Everyday

<|channel|>analysis<|message|>Need to explain how democracy functions in modern governments. Provide overview of institutions, processes, checks, representation, elections, rule of law, etc.<|end|><|start|>assistant<|channel|>final<|message|>### 1.  What “democracy” means today  
In contemporary politics “democracy” is not a single, fixed model.  It is a **set of practices and institutions** that allow citizens to influence the political process, while also protecting minority rights, the rule of law, and the stability of the state.  Most modern democrans share a few core features:

| Feature | Typical expression in a modern state | Why it matters |
|---|---|---|
| **Representative institutions** (parliament, council, etc.) | Legislators elected by proportional or district‑based ballots | Gives a voice to the electorate in law‑making |
| **Free, competitive elections** | Regular, multi‑party contests with universal suff suff | Determines who will hold office |
| **Rule of law & separation of powers** | Judiciary independent, executive & legislature distinct | Prevents abuse of power |
| **Civil‑society participation** | NGOs, media, protests, public consultation | Allows citizens to shape policy beyond ballots |
| **Checks & balances** | Constitutional limits, oversight bodies, judicial review | Keeps power in check |
| **Protection of minorities** | Quotas, affirmative‑action laws, constitutional safeguards | Prevents tyranny of the majority |

These elements can be arranged in different ways (parliamentary vs. presidential, federal vs. unitary, etc.), but the combination of them is what modern democrans call “democracy.”

---

### 2.  How the system works in practice  

#### 2.1  The electoral cycle  
1. **Campaigning** – Parties and candidates present platforms, debate, and advertise.  
2. **Voting** – Citizens cast ballots (paper, electronic, absentee).  
3. **Counting & certification** – Election commissions verify results.  
4. **Transition** – Newly elected officials assume office, often after a “hand‑over” period.  

The electoral cycle is the most visible democratic mechanism, but it is only one layer of governance.

#### 2.2  Representative bodies  
- **Parliament / Congress**: Drafts laws, debates policy, and holds the executive accountable.  
- **Executive (President, Prime Minister, etc.)**: Implements laws, runs the state, and is usually elected or appointed by the legislature.  
- **