commit 105523fb68dafc1f433a6779e2341e2dff89f27d Author: ModelHub XC Date: Sat Jul 11 22:55:06 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..53d7257 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,47 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bin.* filter=lfs diff=lfs merge=lfs -text +*.bz2 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 +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zstandard filter=lfs diff=lfs merge=lfs -text +*.tfevents* filter=lfs diff=lfs merge=lfs -text +*.db* filter=lfs diff=lfs merge=lfs -text +*.ark* filter=lfs diff=lfs merge=lfs -text +**/*ckpt*data* filter=lfs diff=lfs merge=lfs -text +**/*ckpt*.meta filter=lfs diff=lfs merge=lfs -text +**/*ckpt*.index filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.gguf* filter=lfs diff=lfs merge=lfs -text +*.ggml filter=lfs diff=lfs merge=lfs -text +*.llamafile* filter=lfs diff=lfs merge=lfs -text +*.pt2 filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..e36d293 --- /dev/null +++ b/README.md @@ -0,0 +1,165 @@ +--- +quantized_by: bartowski +pipeline_tag: text-generation +base_model_relation: quantized +base_model: nvidia/NVIDIA-Nemotron-Nano-9B-v2 +--- + +## Llamacpp imatrix Quantizations of NVIDIA-Nemotron-Nano-9B-v2 by nvidia + +Using llama.cpp release b6317 for quantization. + +Original model: https://huggingface.co/nvidia/NVIDIA-Nemotron-Nano-9B-v2 + +All quants made using imatrix option with dataset from [here](https://gist.github.com/bartowski1182/eb213dccb3571f863da82e99418f81e8) combined with a subset of combined_all_small.parquet from Ed Addario [here](https://huggingface.co/datasets/eaddario/imatrix-calibration/blob/main/combined_all_small.parquet) + +Run them in [LM Studio](https://lmstudio.ai/) + +Run them directly with [llama.cpp](https://github.com/ggml-org/llama.cpp), or any other llama.cpp based project + +## Prompt format + +No prompt format found, check original model page + +## Download a file (not the whole branch) from below: + +| Filename | Quant type | File Size | Split | Description | +| -------- | ---------- | --------- | ----- | ----------- | +| [NVIDIA-Nemotron-Nano-9B-v2-bf16.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-bf16.gguf) | bf16 | 17.79GB | false | Full BF16 weights. | +| [NVIDIA-Nemotron-Nano-9B-v2-Q8_0.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q8_0.gguf) | Q8_0 | 9.46GB | false | Extremely high quality, generally unneeded but max available quant. | +| [NVIDIA-Nemotron-Nano-9B-v2-Q6_K_L.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q6_K_L.gguf) | Q6_K_L | 9.14GB | false | Uses Q8_0 for embed and output weights. Very high quality, near perfect, *recommended*. | +| [NVIDIA-Nemotron-Nano-9B-v2-Q6_K.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q6_K.gguf) | Q6_K | 9.14GB | false | Very high quality, near perfect, *recommended*. | +| [NVIDIA-Nemotron-Nano-9B-v2-Q5_K_L.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q5_K_L.gguf) | Q5_K_L | 7.25GB | false | Uses Q8_0 for embed and output weights. High quality, *recommended*. | +| [NVIDIA-Nemotron-Nano-9B-v2-Q5_K_M.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q5_K_M.gguf) | Q5_K_M | 7.07GB | false | High quality, *recommended*. | +| [NVIDIA-Nemotron-Nano-9B-v2-Q5_K_S.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q5_K_S.gguf) | Q5_K_S | 6.78GB | false | High quality, *recommended*. | +| [NVIDIA-Nemotron-Nano-9B-v2-Q4_K_L.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_K_L.gguf) | Q4_K_L | 6.75GB | false | Uses Q8_0 for embed and output weights. Good quality, *recommended*. | +| [NVIDIA-Nemotron-Nano-9B-v2-Q4_K_M.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_K_M.gguf) | Q4_K_M | 6.53GB | false | Good quality, default size for most use cases, *recommended*. | +| [NVIDIA-Nemotron-Nano-9B-v2-Q4_K_S.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_K_S.gguf) | Q4_K_S | 6.21GB | false | Slightly lower quality with more space savings, *recommended*. | +| [NVIDIA-Nemotron-Nano-9B-v2-Q4_1.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_1.gguf) | Q4_1 | 5.83GB | false | Legacy format, similar performance to Q4_K_S but with improved tokens/watt on Apple silicon. | +| [NVIDIA-Nemotron-Nano-9B-v2-Q3_K_XL.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q3_K_XL.gguf) | Q3_K_XL | 5.78GB | false | Uses Q8_0 for embed and output weights. Lower quality but usable, good for low RAM availability. | +| [NVIDIA-Nemotron-Nano-9B-v2-Q3_K_L.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q3_K_L.gguf) | Q3_K_L | 5.49GB | false | Lower quality but usable, good for low RAM availability. | +| [NVIDIA-Nemotron-Nano-9B-v2-Q3_K_M.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q3_K_M.gguf) | Q3_K_M | 5.38GB | false | Low quality. | +| [NVIDIA-Nemotron-Nano-9B-v2-Q4_0.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_0.gguf) | Q4_0 | 5.34GB | false | Legacy format, offers online repacking for ARM and AVX CPU inference. | +| [NVIDIA-Nemotron-Nano-9B-v2-IQ4_NL.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ4_NL.gguf) | IQ4_NL | 5.31GB | false | Similar to IQ4_XS, but slightly larger. Offers online repacking for ARM CPU inference. | +| [NVIDIA-Nemotron-Nano-9B-v2-Q2_K_L.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q2_K_L.gguf) | Q2_K_L | 5.30GB | false | Uses Q8_0 for embed and output weights. Very low quality but surprisingly usable. | +| [NVIDIA-Nemotron-Nano-9B-v2-IQ4_XS.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ4_XS.gguf) | IQ4_XS | 5.27GB | false | Decent quality, smaller than Q4_K_S with similar performance, *recommended*. | +| [NVIDIA-Nemotron-Nano-9B-v2-IQ3_M.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ3_M.gguf) | IQ3_M | 5.21GB | false | Medium-low quality, new method with decent performance comparable to Q3_K_M. | +| [NVIDIA-Nemotron-Nano-9B-v2-Q3_K_S.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q3_K_S.gguf) | Q3_K_S | 5.13GB | false | Low quality, not recommended. | +| [NVIDIA-Nemotron-Nano-9B-v2-IQ3_XS.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ3_XS.gguf) | IQ3_XS | 5.13GB | false | Lower quality, new method with decent performance, slightly better than Q3_K_S. | +| [NVIDIA-Nemotron-Nano-9B-v2-IQ3_XXS.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ3_XXS.gguf) | IQ3_XXS | 5.07GB | false | Lower quality, new method with decent performance, comparable to Q3 quants. | +| [NVIDIA-Nemotron-Nano-9B-v2-Q2_K.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q2_K.gguf) | Q2_K | 5.01GB | false | Very low quality but surprisingly usable. | +| [NVIDIA-Nemotron-Nano-9B-v2-IQ2_M.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ2_M.gguf) | IQ2_M | 5.00GB | false | Relatively low quality, uses SOTA techniques to be surprisingly usable. | +| [NVIDIA-Nemotron-Nano-9B-v2-IQ2_S.gguf](https://huggingface.co/bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF/blob/main/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ2_S.gguf) | IQ2_S | 4.96GB | false | Low quality, uses SOTA techniques to be usable. | + +## Embed/output weights + +Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. + +## Downloading using huggingface-cli + +
+ Click to view download instructions + +First, make sure you have hugginface-cli installed: + +``` +pip install -U "huggingface_hub[cli]" +``` + +Then, you can target the specific file you want: + +``` +huggingface-cli download bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF --include "nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_K_M.gguf" --local-dir ./ +``` + +If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run: + +``` +huggingface-cli download bartowski/nvidia_NVIDIA-Nemotron-Nano-9B-v2-GGUF --include "nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q8_0/*" --local-dir ./ +``` + +You can either specify a new local-dir (nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q8_0) or download them all in place (./) + +
+ +## ARM/AVX information + +Previously, you would download Q4_0_4_4/4_8/8_8, and these would have their weights interleaved in memory in order to improve performance on ARM and AVX machines by loading up more data in one pass. + +Now, however, there is something called "online repacking" for weights. details in [this PR](https://github.com/ggml-org/llama.cpp/pull/9921). If you use Q4_0 and your hardware would benefit from repacking weights, it will do it automatically on the fly. + +As of llama.cpp build [b4282](https://github.com/ggml-org/llama.cpp/releases/tag/b4282) you will not be able to run the Q4_0_X_X files and will instead need to use Q4_0. + +Additionally, if you want to get slightly better quality for , you can use IQ4_NL thanks to [this PR](https://github.com/ggml-org/llama.cpp/pull/10541) which will also repack the weights for ARM, though only the 4_4 for now. The loading time may be slower but it will result in an overall speed incrase. + +
+ Click to view Q4_0_X_X information (deprecated + +I'm keeping this section to show the potential theoretical uplift in performance from using the Q4_0 with online repacking. + +
+ Click to view benchmarks on an AVX2 system (EPYC7702) + +| model | size | params | backend | threads | test | t/s | % (vs Q4_0) | +| ------------------------------ | ---------: | ---------: | ---------- | ------: | ------------: | -------------------: |-------------: | +| qwen2 3B Q4_0 | 1.70 GiB | 3.09 B | CPU | 64 | pp512 | 204.03 ± 1.03 | 100% | +| qwen2 3B Q4_0 | 1.70 GiB | 3.09 B | CPU | 64 | pp1024 | 282.92 ± 0.19 | 100% | +| qwen2 3B Q4_0 | 1.70 GiB | 3.09 B | CPU | 64 | pp2048 | 259.49 ± 0.44 | 100% | +| qwen2 3B Q4_0 | 1.70 GiB | 3.09 B | CPU | 64 | tg128 | 39.12 ± 0.27 | 100% | +| qwen2 3B Q4_0 | 1.70 GiB | 3.09 B | CPU | 64 | tg256 | 39.31 ± 0.69 | 100% | +| qwen2 3B Q4_0 | 1.70 GiB | 3.09 B | CPU | 64 | tg512 | 40.52 ± 0.03 | 100% | +| qwen2 3B Q4_K_M | 1.79 GiB | 3.09 B | CPU | 64 | pp512 | 301.02 ± 1.74 | 147% | +| qwen2 3B Q4_K_M | 1.79 GiB | 3.09 B | CPU | 64 | pp1024 | 287.23 ± 0.20 | 101% | +| qwen2 3B Q4_K_M | 1.79 GiB | 3.09 B | CPU | 64 | pp2048 | 262.77 ± 1.81 | 101% | +| qwen2 3B Q4_K_M | 1.79 GiB | 3.09 B | CPU | 64 | tg128 | 18.80 ± 0.99 | 48% | +| qwen2 3B Q4_K_M | 1.79 GiB | 3.09 B | CPU | 64 | tg256 | 24.46 ± 3.04 | 83% | +| qwen2 3B Q4_K_M | 1.79 GiB | 3.09 B | CPU | 64 | tg512 | 36.32 ± 3.59 | 90% | +| qwen2 3B Q4_0_8_8 | 1.69 GiB | 3.09 B | CPU | 64 | pp512 | 271.71 ± 3.53 | 133% | +| qwen2 3B Q4_0_8_8 | 1.69 GiB | 3.09 B | CPU | 64 | pp1024 | 279.86 ± 45.63 | 100% | +| qwen2 3B Q4_0_8_8 | 1.69 GiB | 3.09 B | CPU | 64 | pp2048 | 320.77 ± 5.00 | 124% | +| qwen2 3B Q4_0_8_8 | 1.69 GiB | 3.09 B | CPU | 64 | tg128 | 43.51 ± 0.05 | 111% | +| qwen2 3B Q4_0_8_8 | 1.69 GiB | 3.09 B | CPU | 64 | tg256 | 43.35 ± 0.09 | 110% | +| qwen2 3B Q4_0_8_8 | 1.69 GiB | 3.09 B | CPU | 64 | tg512 | 42.60 ± 0.31 | 105% | + +Q4_0_8_8 offers a nice bump to prompt processing and a small bump to text generation + +
+ +
+ +## Which file should I choose? + +
+ Click here for details + +A great write up with charts showing various performances is provided by Artefact2 [here](https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9) + +The first thing to figure out is how big a model you can run. To do this, you'll need to figure out how much RAM and/or VRAM you have. + +If you want your model running as FAST as possible, you'll want to fit the whole thing on your GPU's VRAM. Aim for a quant with a file size 1-2GB smaller than your GPU's total VRAM. + +If you want the absolute maximum quality, add both your system RAM and your GPU's VRAM together, then similarly grab a quant with a file size 1-2GB Smaller than that total. + +Next, you'll need to decide if you want to use an 'I-quant' or a 'K-quant'. + +If you don't want to think too much, grab one of the K-quants. These are in format 'QX_K_X', like Q5_K_M. + +If you want to get more into the weeds, you can check out this extremely useful feature chart: + +[llama.cpp feature matrix](https://github.com/ggml-org/llama.cpp/wiki/Feature-matrix) + +But basically, if you're aiming for below Q4, and you're running cuBLAS (Nvidia) or rocBLAS (AMD), you should look towards the I-quants. These are in format IQX_X, like IQ3_M. These are newer and offer better performance for their size. + +These I-quants can also be used on CPU, but will be slower than their K-quant equivalent, so speed vs performance is a tradeoff you'll have to decide. + +
+ +## Credits + +Thank you kalomaze and Dampf for assistance in creating the imatrix calibration dataset. + +Thank you ZeroWw for the inspiration to experiment with embed/output. + +Thank you to LM Studio for sponsoring my work. + +Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski diff --git a/configuration.json b/configuration.json new file mode 100644 index 0000000..bbeeda1 --- /dev/null +++ b/configuration.json @@ -0,0 +1 @@ +{"framework": "pytorch", "task": "text-generation", "allow_remote": true} \ No newline at end of file diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ2_M.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ2_M.gguf new file mode 100644 index 0000000..d9548e5 --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ2_M.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bd48428408ed93efb7bf0bab8a26e610b4e06e5bc4aafe011d783987f00aa5ca +size 4996515680 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ2_S.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ2_S.gguf new file mode 100644 index 0000000..8d62d5c --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ2_S.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8a31bde795884c4a32bfa9208b8605e57acce38814b981f611d56ea201a910a2 +size 4957808480 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ3_M.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ3_M.gguf new file mode 100644 index 0000000..bf770ef --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ3_M.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6be313382440dcf3d89f3a491716b68093ce5ee1a2d7dc8cd5d29cd0aea23a91 +size 5207935840 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ3_XS.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ3_XS.gguf new file mode 100644 index 0000000..2b25136 --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ3_XS.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e6c2652a5cfa135a0f50cc512864fdb3488b0e94e0d820afc9f7c9e0a8f23eb9 +size 5131990880 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ3_XXS.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ3_XXS.gguf new file mode 100644 index 0000000..c2a98bd --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ3_XXS.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a60d3e176af3929b8781f979774fd5765cb2aae6200561b6c34da2afb5262460 +size 5073930080 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ4_NL.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ4_NL.gguf new file mode 100644 index 0000000..32ddf61 --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ4_NL.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3c408e4a79065b0dc93cdeb982583ed6632bf69d21badde9307c201a24812522 +size 5308682080 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ4_XS.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ4_XS.gguf new file mode 100644 index 0000000..32bace5 --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-IQ4_XS.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4b4e85cae0115a6a6aac311810accc27a605a761feae1ef0aa83be7c5015ba19 +size 5267107680 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q2_K.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q2_K.gguf new file mode 100644 index 0000000..b7e9799 --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q2_K.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7bb683abcf19655bb0e447963f5aa3d29d602864603202144b78e4d641973f36 +size 5006192480 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q2_K_L.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q2_K_L.gguf new file mode 100644 index 0000000..fcd447f --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q2_K_L.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7040e11f2cd5d9986fbdcbac57ba473fbbccc679be0689ae97ec17d7db202b75 +size 5299793760 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q3_K_L.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q3_K_L.gguf new file mode 100644 index 0000000..a24e0da --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q3_K_L.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d289c6aa20e3da30eb01952659b7bb6c918afe36978daac52b581aabb42836b3 +size 5488365920 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q3_K_M.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q3_K_M.gguf new file mode 100644 index 0000000..a661a4b --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q3_K_M.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9174cfdea9161b0100f42ca4f684410c27c0d1a1329e3581286d6788d6fa6204 +size 5379734880 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q3_K_S.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q3_K_S.gguf new file mode 100644 index 0000000..1313e21 --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q3_K_S.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:778c4ad9b0a131671dce9db6b881a732b4f2e188e6149478b94159253894a421 +size 5131990880 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q3_K_XL.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q3_K_XL.gguf new file mode 100644 index 0000000..c2c9c18 --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q3_K_XL.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c1c229b9abc4925000614a31928be5e4d00ca2822f411c97afae2f3dea24222c +size 5781967200 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_0.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_0.gguf new file mode 100644 index 0000000..7292319 --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_0.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:468ea3a6d895ccb5c5b4e4281c7a889e17b3e3ac263339a927e38e8312dc932c +size 5339414880 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_1.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_1.gguf new file mode 100644 index 0000000..a48a005 --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_1.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:25dcc7d5252977909a9b32da18e3a1aadd1fbf51e82dea4be7a1ab97962e0cff +size 5827358560 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_K_L.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_K_L.gguf new file mode 100644 index 0000000..37056a5 --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_K_L.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:eaf3137fc5fc6132439175d8218cd6004c748828f041bfef9414084211120dc7 +size 6745830240 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_K_M.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_K_M.gguf new file mode 100644 index 0000000..5684354 --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_K_M.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:be84528231457f766a35612386e2638d9af10beb10a9d8d23f0cc73c20818da7 +size 6525629280 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_K_S.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_K_S.gguf new file mode 100644 index 0000000..fc378fc --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q4_K_S.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2cfba6891ddd07219daa30e511226684216bb7b0215604f6d49e44808bae6a85 +size 6211617120 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q5_K_L.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q5_K_L.gguf new file mode 100644 index 0000000..36e4e96 --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q5_K_L.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:359e5d955b8ded2fffde671b93dd68158c0c72b3186f31c1ec40efe75f5b6261 +size 7253306720 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q5_K_M.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q5_K_M.gguf new file mode 100644 index 0000000..5ffcea4 --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q5_K_M.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:09dae3403033e80a411f1f9b03c55712f9ea0c4a4302537027d293f3d9718b3d +size 7069805920 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q5_K_S.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q5_K_S.gguf new file mode 100644 index 0000000..c430115 --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q5_K_S.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:47b741b672dafef9dff9de8ca784063c65f786acd83ee0946e1bab55f7715f07 +size 6781562720 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q6_K.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q6_K.gguf new file mode 100644 index 0000000..54f83aa --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q6_K.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:95ee1b5339df8b4c735564cc2297572c972f181222cced619e726ba428adfc83 +size 9135892320 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q6_K_L.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q6_K_L.gguf new file mode 100644 index 0000000..54f83aa --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q6_K_L.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:95ee1b5339df8b4c735564cc2297572c972f181222cced619e726ba428adfc83 +size 9135892320 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q8_0.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q8_0.gguf new file mode 100644 index 0000000..a6f6b3e --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-Q8_0.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5c43a91e9d200cb2444a8ddc4f1b64c06adca98f86ae390e12c23605dfddef1c +size 9458093920 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-bf16.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-bf16.gguf new file mode 100644 index 0000000..d40c5a2 --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-bf16.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8ef005da11f47cf640cec564b3b761759a360b83fc42d33057e981343094d027 +size 17788743232 diff --git a/nvidia_NVIDIA-Nemotron-Nano-9B-v2-imatrix.gguf b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-imatrix.gguf new file mode 100644 index 0000000..7d10e37 --- /dev/null +++ b/nvidia_NVIDIA-Nemotron-Nano-9B-v2-imatrix.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:50c4f52d141f4fbb2a41aa81e8ef354e83831079f6c32f3295b9a7dff670eb7d +size 3921216