commit 774500697bd118e9aa17bc66f8a37df10a1fc6a6 Author: ModelHub XC Date: Sun Oct 25 09:56:15 2026 +0800 初始化项目,由ModelHub XC社区提供模型 Model: second-state/NVIDIA-Nemotron-Nano-9B-v2-GGUF Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..5fc0c9b --- /dev/null +++ b/.gitattributes @@ -0,0 +1,48 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs 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+library_name: transformers +--- + + + +
+ +
+
+ + +# NVIDIA-Nemotron-Nano-9B-v2-GGUF + +## Original Model + +[nvidia/NVIDIA-Nemotron-Nano-9B-v2](https://huggingface.co/nvidia/NVIDIA-Nemotron-Nano-9B-v2) + +## Run with LlamaEdge + +- LlamaEdge version: coming soon + + + +- Prompt template + + - Prompt type: `nemotron-2-chat` + + - Prompt string + - `Thinking` mode + + ```text + System + You are a helpful assistant. + + User + Hi, can you explain what quantum computing is? /think + + Assistant + + The user is asking about quantum computing, I should give a simple explanation. + + Quantum computing uses principles of quantum mechanics, such as superposition and entanglement, to perform computations that would be hard for classical computers. + + + User + That sounds complicated. Can you give me an example? /think + + Assistant + + I should give a concrete example, like Shor’s algorithm or Grover’s algorithm, but in simple terms. + + For example, a quantum computer can factor very large numbers much faster than classical computers, which could break some encryption methods. + + + User + Okay, explain it in a simpler way for a 10-year-old. /think + + Assistant + + ``` + + - `No-thinking` mode + + ```text + System + You are a helpful assistant. + + /no_think + + User + Hi, can you explain what quantum computing is? /no_think + + Assistant + + Quantum computing is a type of computing that uses the rules of quantum mechanics to solve certain problems faster than regular computers. + + + User + That sounds complicated. Can you give me an example? /no_think + + Assistant + + For example, quantum computers could quickly factor very large numbers, which is important for cryptography. + + + User + Okay, explain it even more simply. /no_think + + Assistant + + ``` + +- Context size: `128000` + +- Run as LlamaEdge service + + ```bash + wasmedge --dir .:. \ + --nn-preload default:GGML:AUTO:NVIDIA-Nemotron-Nano-9B-v2-Q5_K_M.gguf \ + llama-api-server.wasm \ + --prompt-template nemotron-2-chat \ + --ctx-size 128000 \ + --model-name nemotron-nano-v2 + ``` + +## Quantized GGUF Models + +| Name | Quant method | Bits | Size | Use case | +| ---- | ---- | ---- | ---- | ----- | +| [NVIDIA-Nemotron-Nano-9B-v2-Q2_K.gguf](https://huggingface.co/second-state/NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/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](https://huggingface.co/second-state/NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/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](https://huggingface.co/second-state/NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/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](https://huggingface.co/second-state/NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/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](https://huggingface.co/second-state/NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/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](https://huggingface.co/second-state/NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/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](https://huggingface.co/second-state/NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/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](https://huggingface.co/second-state/NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/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](https://huggingface.co/second-state/NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/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](https://huggingface.co/second-state/NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/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](https://huggingface.co/second-state/NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/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](https://huggingface.co/second-state/Nemotron-Mini-4B-Instruct-GGUF/blob/main/NVIDIA-Nemotron-Nano-9B-v2-f16.gguf) | Q8_0 | 8 | 17.8 GB| very large, extremely low quality loss - not recommended | +| [NVIDIA-Nemotron-Nano-9B-v2-f16.gguf](https://huggingface.co/second-state/NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/NVIDIA-Nemotron-Nano-9B-v2-f16-00001-of-00003.gguf) | f16 | 16 | 30.0 GB| | + +*Quantized with llama.cpp b6315.* diff --git a/config.json b/config.json new file mode 100644 index 0000000..ed7dc37 --- /dev/null +++ b/config.json @@ -0,0 +1,60 @@ +{ + "architectures": [ + "NemotronHForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "auto_map": { + "AutoConfig": "configuration_nemotron_h.NemotronHConfig", + "AutoModelForCausalLM": "modeling_nemotron_h.NemotronHForCausalLM" + }, + "bos_token_id": 1, + "chunk_size": 128, + "conv_kernel": 4, + "eos_token_id": 12, + "head_dim": 128, + "hidden_dropout": 0.0, + "hidden_size": 4480, + "hybrid_override_pattern": "M-M-M-MM-M-M-M*-M-M-M*-M-M-M-M*-M-M-M-M*-M-MM-M-M-M-M-M-", + "initializer_range": 0.02, + "intermediate_size": 15680, + "layer_norm_epsilon": 1e-05, + "mamba_head_dim": 80, + "mamba_hidden_act": "silu", + "mamba_num_groups": 8, + "mamba_num_heads": 128, + "mamba_proj_bias": false, + "mamba_state_dim": 128, + "max_position_embeddings": 131072, + "mlp_bias": false, + "mlp_hidden_act": "relu2", + "model_type": "nemotron_h", + "n_groups": 8, + "num_attention_heads": 40, + "num_hidden_layers": 56, + "num_key_value_heads": 8, + "num_logits_to_keep": 1, + "num_query_groups": 8, + "pad_token_id": 0, + "rescale_prenorm_residual": true, + "residual_in_fp32": false, + "rms_norm_eps": 1e-05, + "sliding_window": null, + "ssm_state_size": 128, + "tie_word_embeddings": false, + "time_step_floor": 0.0001, + "time_step_limit": [ + 0.0, + Infinity + ], + "time_step_max": 0.1, + "time_step_min": 0.001, + "time_step_rank": 256, + "torch_dtype": "bfloat16", + "transformers_version": "4.51.3", + "use_bias": false, + "use_cache": true, + "use_conv_bias": true, + "use_mamba_kernels": true, + "vocab_size": 131072 +}