bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF
1
0
Fork 0
Code Issues Pull Requests Actions Projects Releases Wiki Activity

初始化项目，由ModelHub XC社区提供模型

Browse Source 
Model: bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF
Source: Original Platform
This commit is contained in:
ModelHub XC
2026-07-21 18:02:07 +08:00
commit 78e8a97144
28 changed files with 321 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

73
.gitattributes vendored Normal file
View File

@@ -0,0 +1,73 @@
*.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
*.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
ai21labs_AI21-Jamba-Reasoning-3B-Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-Q3_K_XL.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-bf16.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-Q4_K_L.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-IQ3_M.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-Q4_1.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-IQ4_XS.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-IQ3_XXS.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-Q5_K_L.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-imatrix.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-Q6_K_L.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-IQ2_M.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-IQ3_XS.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-Q2_K_L.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-IQ4_NL.gguf filter=lfs diff=lfs merge=lfs -text
ai21labs_AI21-Jamba-Reasoning-3B-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text

172
README.md Normal file
View File

@@ -0,0 +1,172 @@
---
quantized_by: bartowski
pipeline_tag: text-generation
base_model: ai21labs/AI21-Jamba-Reasoning-3B
base_model_relation: quantized
---
## Llamacpp imatrix Quantizations of AI21-Jamba-Reasoning-3B by ai21labs
Using <a href="https://github.com/ggml-org/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggml-org/llama.cpp/releases/tag/b6683">b6683</a> for quantization.
Original model: https://huggingface.co/ai21labs/AI21-Jamba-Reasoning-3B
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
```
<|startoftext|><|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
Begin by thinking about the reasoning process in the mind within <think> </think> tags and then proceed to give your response.
{prompt}<|im_end|>
<|im_start|>assistant
<think>
```
## Download a file (not the whole branch) from below:
| Filename | Quant type | File Size | Split | Description |
| -------- | ---------- | --------- | ----- | ----------- |
| [AI21-Jamba-Reasoning-3B-bf16.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-bf16.gguf) | bf16 | 6.40GB | false | Full BF16 weights. |
| [AI21-Jamba-Reasoning-3B-Q8_0.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-Q8_0.gguf) | Q8_0 | 3.41GB | false | Extremely high quality, generally unneeded but max available quant. |
| [AI21-Jamba-Reasoning-3B-Q6_K_L.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-Q6_K_L.gguf) | Q6_K_L | 2.72GB | false | Uses Q8_0 for embed and output weights. Very high quality, near perfect, *recommended*. |
| [AI21-Jamba-Reasoning-3B-Q6_K.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-Q6_K.gguf) | Q6_K | 2.64GB | false | Very high quality, near perfect, *recommended*. |
| [AI21-Jamba-Reasoning-3B-Q5_K_L.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-Q5_K_L.gguf) | Q5_K_L | 2.38GB | false | Uses Q8_0 for embed and output weights. High quality, *recommended*. |
| [AI21-Jamba-Reasoning-3B-Q5_K_M.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-Q5_K_M.gguf) | Q5_K_M | 2.27GB | false | High quality, *recommended*. |
| [AI21-Jamba-Reasoning-3B-Q5_K_S.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-Q5_K_S.gguf) | Q5_K_S | 2.23GB | false | High quality, *recommended*. |
| [AI21-Jamba-Reasoning-3B-Q4_K_L.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-Q4_K_L.gguf) | Q4_K_L | 2.06GB | false | Uses Q8_0 for embed and output weights. Good quality, *recommended*. |
| [AI21-Jamba-Reasoning-3B-Q4_1.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-Q4_1.gguf) | Q4_1 | 2.04GB | false | Legacy format, similar performance to Q4_K_S but with improved tokens/watt on Apple silicon. |
| [AI21-Jamba-Reasoning-3B-Q4_K_M.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-Q4_K_M.gguf) | Q4_K_M | 1.93GB | false | Good quality, default size for most use cases, *recommended*. |
| [AI21-Jamba-Reasoning-3B-Q4_K_S.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-Q4_K_S.gguf) | Q4_K_S | 1.86GB | false | Slightly lower quality with more space savings, *recommended*. |
| [AI21-Jamba-Reasoning-3B-Q4_0.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-Q4_0.gguf) | Q4_0 | 1.86GB | false | Legacy format, offers online repacking for ARM and AVX CPU inference. |
| [AI21-Jamba-Reasoning-3B-IQ4_NL.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-IQ4_NL.gguf) | IQ4_NL | 1.85GB | false | Similar to IQ4_XS, but slightly larger. Offers online repacking for ARM CPU inference. |
| [AI21-Jamba-Reasoning-3B-IQ4_XS.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-IQ4_XS.gguf) | IQ4_XS | 1.76GB | false | Decent quality, smaller than Q4_K_S with similar performance, *recommended*. |
| [AI21-Jamba-Reasoning-3B-Q3_K_XL.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-Q3_K_XL.gguf) | Q3_K_XL | 1.76GB | false | Uses Q8_0 for embed and output weights. Lower quality but usable, good for low RAM availability. |
| [AI21-Jamba-Reasoning-3B-Q3_K_L.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-Q3_K_L.gguf) | Q3_K_L | 1.61GB | false | Lower quality but usable, good for low RAM availability. |
| [AI21-Jamba-Reasoning-3B-Q3_K_M.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-Q3_K_M.gguf) | Q3_K_M | 1.54GB | false | Low quality. |
| [AI21-Jamba-Reasoning-3B-IQ3_M.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-IQ3_M.gguf) | IQ3_M | 1.47GB | false | Medium-low quality, new method with decent performance comparable to Q3_K_M. |
| [AI21-Jamba-Reasoning-3B-Q3_K_S.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-Q3_K_S.gguf) | Q3_K_S | 1.46GB | false | Low quality, not recommended. |
| [AI21-Jamba-Reasoning-3B-IQ3_XS.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-IQ3_XS.gguf) | IQ3_XS | 1.41GB | false | Lower quality, new method with decent performance, slightly better than Q3_K_S. |
| [AI21-Jamba-Reasoning-3B-Q2_K_L.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-Q2_K_L.gguf) | Q2_K_L | 1.37GB | false | Uses Q8_0 for embed and output weights. Very low quality but surprisingly usable. |
| [AI21-Jamba-Reasoning-3B-IQ3_XXS.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-IQ3_XXS.gguf) | IQ3_XXS | 1.30GB | false | Lower quality, new method with decent performance, comparable to Q3 quants. |
| [AI21-Jamba-Reasoning-3B-Q2_K.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-Q2_K.gguf) | Q2_K | 1.21GB | false | Very low quality but surprisingly usable. |
| [AI21-Jamba-Reasoning-3B-IQ2_M.gguf](https://huggingface.co/bartowski/ai21labs_AI21-Jamba-Reasoning-3B-GGUF/blob/main/ai21labs_AI21-Jamba-Reasoning-3B-IQ2_M.gguf) | IQ2_M | 1.13GB | 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/ai21labs_AI21-Jamba-Reasoning-3B-GGUF --include "ai21labs_AI21-Jamba-Reasoning-3B-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/ai21labs_AI21-Jamba-Reasoning-3B-GGUF --include "ai21labs_AI21-Jamba-Reasoning-3B-Q8_0/*" --local-dir ./
```
You can either specify a new local-dir (ai21labs_AI21-Jamba-Reasoning-3B-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/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.
<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/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.
</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

3
ai21labs_AI21-Jamba-Reasoning-3B-IQ2_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:a184e6ae2196c3f87eb9141f9bf6f663bc330f4258ae3167701f11efc4413686
size 1130980832

3
ai21labs_AI21-Jamba-Reasoning-3B-IQ3_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:398afd100e656b3b3b8bc39ca35c3e912530e82751c0f21b32f4f8babfd94ed2
size 1465362912

3
ai21labs_AI21-Jamba-Reasoning-3B-IQ3_XS.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:9f1a68e100dfe1269424ab5fe0ac95290d4e1b76bcd8426538d5f01eb8ac2edd
size 1413246432

3
ai21labs_AI21-Jamba-Reasoning-3B-IQ3_XXS.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:7a9955b349476de5fa80c056e41d51842dc973412b020f68c66e807b16634865
size 1299664352

3
ai21labs_AI21-Jamba-Reasoning-3B-IQ4_NL.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:f9b8f716a03eaa4c88587443003d26306afaddb6699cc9bbdf18f51945f3a326
size 1854257632

3
ai21labs_AI21-Jamba-Reasoning-3B-IQ4_XS.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:0bc75112f572fe21f8e3da725e72150ee96342d54792c9ddba40d11a124c2b2e
size 1760356832

3
ai21labs_AI21-Jamba-Reasoning-3B-Q2_K.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:9266a85d6312a2482759dca425eb918743a5feed6694b9efdfefb6139dd20ac5
size 1211037152

3
ai21labs_AI21-Jamba-Reasoning-3B-Q2_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:b82c508cccc38b26d91e10762885741adc4a2348e143ded75fca8f9c77081f31
size 1374877152

3
ai21labs_AI21-Jamba-Reasoning-3B-Q3_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:797e9ed74578e1a017e838af79b66f7515f6abee9d6c3456b37ca5f579e1d050
size 1610115552

3
ai21labs_AI21-Jamba-Reasoning-3B-Q3_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:d7707a34c1ebfc4c88529be6b0bbcb819a8496585eee57ea369e29e8878c327a
size 1537698272

3
ai21labs_AI21-Jamba-Reasoning-3B-Q3_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:b254c7bdaa70b28e707780ce583feb25343eba58833a9939ab5dcee5224d346d
size 1455179232

3
ai21labs_AI21-Jamba-Reasoning-3B-Q3_K_XL.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:2d2847b31e3ea96660a30e6458170d4e9be1ab96e073f89dbbd20ef0c141374f
size 1756916192

3
ai21labs_AI21-Jamba-Reasoning-3B-Q4_0.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:de6fe6a099157fbdd17c0935335f23faf3b33e1e18a171c569a04b1c1333c2d2
size 1858189792

3
ai21labs_AI21-Jamba-Reasoning-3B-Q4_1.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:d6abab7e4e4e0026b065741b21d8813f6444fbe64c0bc57f973cce621f23edf5
size 2043390432

3
ai21labs_AI21-Jamba-Reasoning-3B-Q4_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:022194e4dafd8d13755883f026139dd6779969421c6e438c1abc253cd8fdb262
size 2057216992

3
ai21labs_AI21-Jamba-Reasoning-3B-Q4_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:ac7ec0648dea62d1efb5ef6e7268c748ffc71f1c26eebe97eccff0a8d41608e6
size 1932698592

3
ai21labs_AI21-Jamba-Reasoning-3B-Q4_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:8b385b1147fbea058291d3fb578bca3a613502acce3af8bbc0624b75900577d2
size 1864866272

3
ai21labs_AI21-Jamba-Reasoning-3B-Q5_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:d8fc85b6ee478553a5b1096a19b2233bc4a745026834b57817895addf2703603
size 2376438752

3
ai21labs_AI21-Jamba-Reasoning-3B-Q5_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:f4d8d24912327c41993827afbe3c700c6bcece5d48093dce4eb20824f27ea962
size 2272891872

3
ai21labs_AI21-Jamba-Reasoning-3B-Q5_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:229114da7e3d41635394fccd99691546a158fbb61286a9ca039cb89ca5a85a44
size 2233854432

3
ai21labs_AI21-Jamba-Reasoning-3B-Q6_K.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:5ddf4fe37906e173017c11ca08792875e751bca88cc62bd858e13cebd070d2f4
size 2639588832

3
ai21labs_AI21-Jamba-Reasoning-3B-Q6_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:7adb0c23e08827a2b54ced2117470ddc41e3c78cbd4615e75fc2e2f0421b5b84
size 2720853472

3
ai21labs_AI21-Jamba-Reasoning-3B-Q8_0.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:a6ce2452d5b1ddd4279607a44ff1b580bfae57695bdcb09b394a7b5e089bb8ff
size 3407952352

3
ai21labs_AI21-Jamba-Reasoning-3B-bf16.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:8f48bd3964ebd1cf84ddcc882ac73be70a7174edfc2be14c6d93a01d962c4382
size 6402230464

3
ai21labs_AI21-Jamba-Reasoning-3B-imatrix.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:8647d05cb0639830848b14fe0018753e7e6a6e5dd7cf02f1a662e26677cc333c
size 2950624

1
configuration.json Normal file
View File

@@ -0,0 +1 @@
{"framework": "pytorch", "task": "text-generation", "allow_remote": true}