初始化项目，由ModelHub XC社区提供模型

Model: bartowski/nvidia_OpenMath-Nemotron-7B-GGUF Source: Original Platform
2026-09-28 21:33:15 +08:00
commit a7d4cec576
28 changed files with 298 additions and 0 deletions
--- a/.gitattributes
+++ 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
--- a/README.md
+++ b/README.md
@@ -0,0 +1,178 @@
+---
+quantized_by: bartowski
+pipeline_tag: text-generation
+datasets:
+- nvidia/OpenMathReasoning
+language:
+- en
+license: cc-by-4.0
+tags:
+- nvidia
+- math
+base_model: nvidia/OpenMath-Nemotron-7B
+base_model_relation: quantized
+---
+
+## Llamacpp imatrix Quantizations of OpenMath-Nemotron-7B by nvidia
+
+Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b5192">b5192</a> for quantization.
+
+Original model: https://huggingface.co/nvidia/OpenMath-Nemotron-7B
+
+All quants made using imatrix option with dataset from [here](https://gist.github.com/bartowski1182/eb213dccb3571f863da82e99418f81e8)
+
+Run them in [LM Studio](https://lmstudio.ai/)
+
+Run them directly with [llama.cpp](https://github.com/ggerganov/llama.cpp), or any other llama.cpp based project
+
+## Prompt format
+
+```
+<|im_start|>system
+{system_prompt}<|im_end|>
+<|im_start|>user
+{prompt}<|im_end|>
+<|im_start|>assistant
+```
+
+## Download a file (not the whole branch) from below:
+
+| Filename | Quant type | File Size | Split | Description |
+| -------- | ---------- | --------- | ----- | ----------- |
+| [OpenMath-Nemotron-7B-bf16.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-bf16.gguf) | bf16 | 15.24GB | false | Full BF16 weights. |
+| [OpenMath-Nemotron-7B-Q8_0.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-Q8_0.gguf) | Q8_0 | 8.10GB | false | Extremely high quality, generally unneeded but max available quant. |
+| [OpenMath-Nemotron-7B-Q6_K_L.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-Q6_K_L.gguf) | Q6_K_L | 6.52GB | false | Uses Q8_0 for embed and output weights. Very high quality, near perfect, *recommended*. |
+| [OpenMath-Nemotron-7B-Q6_K.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-Q6_K.gguf) | Q6_K | 6.25GB | false | Very high quality, near perfect, *recommended*. |
+| [OpenMath-Nemotron-7B-Q5_K_L.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-Q5_K_L.gguf) | Q5_K_L | 5.78GB | false | Uses Q8_0 for embed and output weights. High quality, *recommended*. |
+| [OpenMath-Nemotron-7B-Q5_K_M.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-Q5_K_M.gguf) | Q5_K_M | 5.44GB | false | High quality, *recommended*. |
+| [OpenMath-Nemotron-7B-Q5_K_S.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-Q5_K_S.gguf) | Q5_K_S | 5.32GB | false | High quality, *recommended*. |
+| [OpenMath-Nemotron-7B-Q4_K_L.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-Q4_K_L.gguf) | Q4_K_L | 5.09GB | false | Uses Q8_0 for embed and output weights. Good quality, *recommended*. |
+| [OpenMath-Nemotron-7B-Q4_1.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-Q4_1.gguf) | Q4_1 | 4.87GB | false | Legacy format, similar performance to Q4_K_S but with improved tokens/watt on Apple silicon. |
+| [OpenMath-Nemotron-7B-Q4_K_M.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-Q4_K_M.gguf) | Q4_K_M | 4.68GB | false | Good quality, default size for most use cases, *recommended*. |
+| [OpenMath-Nemotron-7B-Q3_K_XL.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-Q3_K_XL.gguf) | Q3_K_XL | 4.57GB | false | Uses Q8_0 for embed and output weights. Lower quality but usable, good for low RAM availability. |
+| [OpenMath-Nemotron-7B-Q4_K_S.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-Q4_K_S.gguf) | Q4_K_S | 4.46GB | false | Slightly lower quality with more space savings, *recommended*. |
+| [OpenMath-Nemotron-7B-Q4_0.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-Q4_0.gguf) | Q4_0 | 4.44GB | false | Legacy format, offers online repacking for ARM and AVX CPU inference. |
+| [OpenMath-Nemotron-7B-IQ4_NL.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-IQ4_NL.gguf) | IQ4_NL | 4.44GB | false | Similar to IQ4_XS, but slightly larger. Offers online repacking for ARM CPU inference. |
+| [OpenMath-Nemotron-7B-IQ4_XS.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-IQ4_XS.gguf) | IQ4_XS | 4.22GB | false | Decent quality, smaller than Q4_K_S with similar performance, *recommended*. |
+| [OpenMath-Nemotron-7B-Q3_K_L.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-Q3_K_L.gguf) | Q3_K_L | 4.09GB | false | Lower quality but usable, good for low RAM availability. |
+| [OpenMath-Nemotron-7B-Q3_K_M.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-Q3_K_M.gguf) | Q3_K_M | 3.81GB | false | Low quality. |
+| [OpenMath-Nemotron-7B-IQ3_M.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-IQ3_M.gguf) | IQ3_M | 3.57GB | false | Medium-low quality, new method with decent performance comparable to Q3_K_M. |
+| [OpenMath-Nemotron-7B-Q2_K_L.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-Q2_K_L.gguf) | Q2_K_L | 3.55GB | false | Uses Q8_0 for embed and output weights. Very low quality but surprisingly usable. |
+| [OpenMath-Nemotron-7B-Q3_K_S.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-Q3_K_S.gguf) | Q3_K_S | 3.49GB | false | Low quality, not recommended. |
+| [OpenMath-Nemotron-7B-IQ3_XS.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-IQ3_XS.gguf) | IQ3_XS | 3.35GB | false | Lower quality, new method with decent performance, slightly better than Q3_K_S. |
+| [OpenMath-Nemotron-7B-IQ3_XXS.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-IQ3_XXS.gguf) | IQ3_XXS | 3.11GB | false | Lower quality, new method with decent performance, comparable to Q3 quants. |
+| [OpenMath-Nemotron-7B-Q2_K.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-Q2_K.gguf) | Q2_K | 3.02GB | false | Very low quality but surprisingly usable. |
+| [OpenMath-Nemotron-7B-IQ2_M.gguf](https://huggingface.co/bartowski/nvidia_OpenMath-Nemotron-7B-GGUF/blob/main/nvidia_OpenMath-Nemotron-7B-IQ2_M.gguf) | IQ2_M | 2.78GB | false | Relatively low quality, uses SOTA techniques to be surprisingly 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
+
+<details>
+  <summary>Click to view download instructions</summary>
+
+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_OpenMath-Nemotron-7B-GGUF --include "nvidia_OpenMath-Nemotron-7B-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_OpenMath-Nemotron-7B-GGUF --include "nvidia_OpenMath-Nemotron-7B-Q8_0/*" --local-dir ./
+```
+
+You can either specify a new local-dir (nvidia_OpenMath-Nemotron-7B-Q8_0) or download them all in place (./)
+
+</details>
+
+## 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/ggerganov/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/ggerganov/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/ggerganov/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.
+
+<details>
+  <summary>Click to view Q4_0_X_X information (deprecated</summary>
+
+I'm keeping this section to show the potential theoretical uplift in performance from using the Q4_0 with online repacking.
+
+<details>
+  <summary>Click to view benchmarks on an AVX2 system (EPYC7702)</summary>
+
+| 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
+
+</details>
+
+</details>
+
+## Which file should I choose?
+
+<details>
+  <summary>Click here for details</summary>
+
+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/ggerganov/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.
+
+</details>
+
+## 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
--- a/configuration.json
+++ b/configuration.json
@@ -0,0 +1 @@
+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
--- a/nvidia_OpenMath-Nemotron-7B-IQ2_M.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-IQ2_M.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:645336a7e233f8a6c57159acfb8ec3792b63bec24cad085ae2542ae5e7446085
+size 2780341152
--- a/nvidia_OpenMath-Nemotron-7B-IQ3_M.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-IQ3_M.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:54082a0a58c70bedc2c0f5f038958f765ed1199a90e0964772350c5b4c609b28
+size 3574010784
--- a/nvidia_OpenMath-Nemotron-7B-IQ3_XS.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-IQ3_XS.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e951d2de5c7af7035b11ca98d0d79a1cd600dfda5955249ef092e00676175496
+size 3346254752
--- a/nvidia_OpenMath-Nemotron-7B-IQ3_XXS.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-IQ3_XXS.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2ec7c48c5a89acea1f9eb54c58e8e17c01e9ad3492d17ebdce8cedbefa2fe1a7
+size 3114513312
--- a/nvidia_OpenMath-Nemotron-7B-IQ4_NL.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-IQ4_NL.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:92b012bab73069d3f2865f4136d78f274da312c9a60b81a94099c2a43f2293e5
+size 4437812128
--- a/nvidia_OpenMath-Nemotron-7B-IQ4_XS.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-IQ4_XS.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:faeb5b19036fb6be99342c5347c142f028d09f139447839653f6b3cf99090d69
+size 4218471328
--- a/nvidia_OpenMath-Nemotron-7B-Q2_K.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-Q2_K.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6749158e1217e654eb06b3c92d4cf78ccf57253a46bfa37e0e275347d28b9d8b
+size 3015938976
--- a/nvidia_OpenMath-Nemotron-7B-Q2_K_L.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-Q2_K_L.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:46448e8213c8d999be5a82b4b7acd8c70c77b164cdb8abcc246fbad3d294ee4a
+size 3548162976
--- a/nvidia_OpenMath-Nemotron-7B-Q3_K_L.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-Q3_K_L.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ef43ec90f36d540d19b2fb7fdc7e92942b97338c19c07dfeac22a17b5a16f4bf
+size 4088458144
--- a/nvidia_OpenMath-Nemotron-7B-Q3_K_M.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-Q3_K_M.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b3970e42c3b65bd77fa9c79f9100cd1e7c8f3cf2c88799d13ed523a30b7674eb
+size 3808390048
--- a/nvidia_OpenMath-Nemotron-7B-Q3_K_S.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-Q3_K_S.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d619a43ff9acc66f5bc65df4f95882b45b821c81badd6e5cf91a4a5b436833dc
+size 3492367264
--- a/nvidia_OpenMath-Nemotron-7B-Q3_K_XL.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-Q3_K_XL.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:38824d4fac0a9414d8a5448cfdf45ea2db832311fda702a0162de5062bf85523
+size 4565330848
--- a/nvidia_OpenMath-Nemotron-7B-Q4_0.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-Q4_0.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0d19bc5d7d8b6ed04b891fc5e66a80132a7dca4812c43f0b613d6215f761f952
+size 4444119968
--- a/nvidia_OpenMath-Nemotron-7B-Q4_1.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-Q4_1.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:129de31cc742fd0a3fc2ac1471f67ba2f3927a1a58189f7cc8749d506e45f7ff
+size 4873282464
--- a/nvidia_OpenMath-Nemotron-7B-Q4_K_L.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-Q4_K_L.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d6080f0cc4268f67bc2322c600b5faf106c123e2531c9be558c31a443750e2a3
+size 5087562656
--- a/nvidia_OpenMath-Nemotron-7B-Q4_K_M.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-Q4_K_M.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e205dd86ab9c73614d88dc3a84bd1a4e94255528f9ddb33e739ea23830342ee4
+size 4683072416
--- a/nvidia_OpenMath-Nemotron-7B-Q4_K_S.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-Q4_K_S.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1cc75a9c9fe1300e200824df2aaa27fbf1772cf7ee30b4718b5b2aa3e28d1114
+size 4457767840
--- a/nvidia_OpenMath-Nemotron-7B-Q5_K_L.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-Q5_K_L.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3841417844c76617940379ab386823d13786a36a18c6e1213566013bddf71b83
+size 5781195680
--- a/nvidia_OpenMath-Nemotron-7B-Q5_K_M.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-Q5_K_M.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:18d98e6009b5bab3dbe942dc628f6e78176fcaa5ecac9098c658d2f16b9b83dc
+size 5444830112
--- a/nvidia_OpenMath-Nemotron-7B-Q5_K_S.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-Q5_K_S.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a4b856d402509f44ada2de6404e2532724a53cf4c9360f13ea1f427e44f08386
+size 5315175328
--- a/nvidia_OpenMath-Nemotron-7B-Q6_K.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-Q6_K.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dba7ab5d931931d6c2553a79eb97f0422113ecf6636dc5d42ae9b48428033aad
+size 6254197664
--- a/nvidia_OpenMath-Nemotron-7B-Q6_K_L.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-Q6_K_L.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:29da10dc01d724d6fcc916eabd44442ddeafdeae20dc4ca2c3be2f363719c18a
+size 6518180768
--- a/nvidia_OpenMath-Nemotron-7B-Q8_0.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-Q8_0.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:02beb1ad2b5836f802ad2166ffef35395a7d05933f4e2b6ef2efa270049ecf52
+size 8098524064
--- a/nvidia_OpenMath-Nemotron-7B-bf16.gguf
+++ b/nvidia_OpenMath-Nemotron-7B-bf16.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:270ab142fab6712374505c54fcea661abaf978a30de19ba2b7053b62166cddc3
+size 15237851776
--- a/nvidia_OpenMath-Nemotron-7B.imatrix
+++ b/nvidia_OpenMath-Nemotron-7B.imatrix
				`@@ -0,0 +1 @@`
				`{"framework": "pytorch", "task": "text-generation", "allow_remote": true}`