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Model: OMCHOKSI108/VibeThinker-3B
Source: Original Platform

USAGE.md

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+# Usage Guide
+
+## Requirements
+
+- Python 3.10+
+- transformers >= 4.54.0
+- CUDA-capable GPU with 8GB+ VRAM (for bfloat16 inference)
+
+## Installation
+
+```bash
+pip install transformers>=4.54.0 torch
+```
+
+For better performance with vLLM:
+
+```bash
+pip install vllm==0.10.1
+```
+
+## Loading the Model
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained(
+    "OMCHOKSI108/VibeThinker-3B",
+    low_cpu_mem_usage=True,
+    torch_dtype="bfloat16",
+    device_map="auto",
+)
+tokenizer = AutoTokenizer.from_pretrained(
+    "OMCHOKSI108/VibeThinker-3B",
+    trust_remote_code=True,
+)
+```
+
+## Basic Inference
+
+```python
+from transformers import GenerationConfig
+
+messages = [{"role": "user", "content": "Solve for x: 3x + 7 = 22"}]
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer([text], return_tensors="pt").to(model.device)
+
+outputs = model.generate(
+    **inputs,
+    generation_config=GenerationConfig(
+        max_new_tokens=40960,
+        do_sample=True,
+        temperature=0.6,
+        top_p=0.95,
+        top_k=None,
+    ),
+)
+response = tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)
+print(response)
+```
+
+## Recommended Parameters
+
+| Parameter | Value | Notes |
+|-----------|-------|-------|
+| temperature | 0.6 or 1.0 | Lower for focused answers, higher for diversity |
+| top_p | 0.95 | Nucleus sampling threshold |
+| top_k | None (or -1 in vLLM/SGLang) | Skip top-k filtering |
+| max_new_tokens | 40960-102400 | Longer for complex reasoning tasks |
+
+## Using with vLLM
+
+```python
+from vllm import LLM, SamplingParams
+
+llm = LLM("OMCHOKSI108/VibeThinker-3B", dtype="bfloat16")
+params = SamplingParams(temperature=0.6, top_p=0.95, top_k=-1, max_tokens=40960)
+output = llm.generate("What is the derivative of x^3?", params)
+print(output[0].outputs[0].text)
+```
+
+## Hardware Requirements
+
+- **Minimum:** 8 GB VRAM (bfloat16, 3B model)
+- **Recommended:** 16 GB+ VRAM (allows larger batch sizes or longer sequences)
+- **CPU inference:** Possible but significantly slower
+
+## Important Notes
+
+1. This model is optimized for verifiable reasoning tasks (math, code, STEM).
+2. It is not designed for tool-calling, agent-based programming, or function calling.
+3. For open-domain knowledge tasks, larger models may be more suitable.
+4. See the [original model card](./ORIGINAL_README.md) for further guidance from the authors.