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nemotron-2-chatThinking mode1<SPECIAL_10>System
2You are a helpful assistant.
3
4<SPECIAL_11>User
5Hi, can you explain what quantum computing is? /think
6
7<SPECIAL_11>Assistant
8<think>
9The user is asking about quantum computing, I should give a simple explanation.
10</think>
11Quantum computing uses principles of quantum mechanics, such as superposition and entanglement, to perform computations that would be hard for classical computers.
12<SPECIAL_12>
13
14<SPECIAL_11>User
15That sounds complicated. Can you give me an example? /think
16
17<SPECIAL_11>Assistant
18<think>
19I should give a concrete example, like Shor’s algorithm or Grover’s algorithm, but in simple terms.
20</think>
21For example, a quantum computer can factor very large numbers much faster than classical computers, which could break some encryption methods.
22<SPECIAL_12>
23
24<SPECIAL_11>User
25Okay, explain it in a simpler way for a 10-year-old. /think
26
27<SPECIAL_11>Assistant
28<think>No-thinking mode1<SPECIAL_10>System
2You are a helpful assistant.
3
4/no_think
5
6<SPECIAL_11>User
7Hi, can you explain what quantum computing is? /no_think
8
9<SPECIAL_11>Assistant
10<think></think>
11Quantum computing is a type of computing that uses the rules of quantum mechanics to solve certain problems faster than regular computers.
12<SPECIAL_12>
13
14<SPECIAL_11>User
15That sounds complicated. Can you give me an example? /no_think
16
17<SPECIAL_11>Assistant
18<think></think>
19For example, quantum computers could quickly factor very large numbers, which is important for cryptography.
20<SPECIAL_12>
21
22<SPECIAL_11>User
23Okay, explain it even more simply. /no_think
24
25<SPECIAL_11>Assistant
26<think></think>1280001wasmedge --dir .:. \
2 --nn-preload default:GGML:AUTO:NVIDIA-Nemotron-Nano-9B-v2-Q5_K_M.gguf \
3 llama-api-server.wasm \
4 --prompt-template nemotron-2-chat \
5 --ctx-size 128000 \
6 --model-name nemotron-nano-v2| Name | Quant method | Bits | Size | Use case |
|---|---|---|---|---|
| NVIDIA-Nemotron-Nano-9B-v2-Q2_K.gguf | Q2_K | 2 | 5.01 GB | smallest, significant quality loss - not recommended for most purposes |
| NVIDIA-Nemotron-Nano-9B-v2-Q3_K_L.gguf | Q3_K_L | 3 | 5.49 GB | small, substantial quality loss |
| NVIDIA-Nemotron-Nano-9B-v2-Q3_K_M.gguf | Q3_K_M | 3 | 5.38 GB | very small, high quality loss |
| NVIDIA-Nemotron-Nano-9B-v2-Q3_K_S.gguf | Q3_K_S | 3 | 5.13 GB | very small, high quality loss |
| NVIDIA-Nemotron-Nano-9B-v2-Q4_0.gguf | Q4_0 | 4 | 5.31 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| NVIDIA-Nemotron-Nano-9B-v2-Q4_K_M.gguf | Q4_K_M | 4 | 6.53 GB | medium, balanced quality - recommended |
| NVIDIA-Nemotron-Nano-9B-v2-Q4_K_S.gguf | Q4_K_S | 4 | 6.21 GB | small, greater quality loss |
| NVIDIA-Nemotron-Nano-9B-v2-Q5_0.gguf | Q5_0 | 5 | 6.35 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| NVIDIA-Nemotron-Nano-9B-v2-Q5_K_M.gguf | Q5_K_M | 5 | 7.07 GB | large, very low quality loss - recommended |
| NVIDIA-Nemotron-Nano-9B-v2-Q5_K_S.gguf | Q5_K_S | 5 | 6.78 GB | large, low quality loss - recommended |
| NVIDIA-Nemotron-Nano-9B-v2-Q6_K.gguf | Q6_K | 6 | 9.14 GB | very large, extremely low quality loss |
| NVIDIA-Nemotron-Nano-9B-v2-Q8_0.gguf | Q8_0 | 8 | 17.8 GB | very large, extremely low quality loss - not recommended |
| NVIDIA-Nemotron-Nano-9B-v2-f16.gguf | f16 | 16 | 30.0 GB |