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Model: bartowski/inclusionAI_Ling-lite-GGUF Source: Original Platform
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---
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quantized_by: bartowski
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pipeline_tag: text-generation
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base_model_relation: quantized
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base_model: inclusionAI/Ling-lite
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license: mit
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---
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## Llamacpp imatrix Quantizations of Ling-lite by inclusionAI
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Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b5035">b5035</a> for quantization.
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Original model: https://huggingface.co/inclusionAI/Ling-lite
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All quants made using imatrix option with dataset from [here](https://gist.github.com/bartowski1182/eb213dccb3571f863da82e99418f81e8)
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Run them in [LM Studio](https://lmstudio.ai/)
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Run them directly with [llama.cpp](https://github.com/ggerganov/llama.cpp), or any other llama.cpp based project
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## Prompt format
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```
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<role>SYSTEM</role>{system_prompt}<role>HUMAN</role>{prompt}<role>ASSISTANT</role><role>ASSISTANT</role>
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```
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## Download a file (not the whole branch) from below:
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| Filename | Quant type | File Size | Split | Description |
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| -------- | ---------- | --------- | ----- | ----------- |
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| [Ling-lite-bf16.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-bf16.gguf) | bf16 | 33.62GB | false | Full BF16 weights. |
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| [Ling-lite-Q8_0.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-Q8_0.gguf) | Q8_0 | 17.87GB | false | Extremely high quality, generally unneeded but max available quant. |
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| [Ling-lite-Q6_K_L.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-Q6_K_L.gguf) | Q6_K_L | 15.18GB | false | Uses Q8_0 for embed and output weights. Very high quality, near perfect, *recommended*. |
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| [Ling-lite-Q6_K.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-Q6_K.gguf) | Q6_K | 15.05GB | false | Very high quality, near perfect, *recommended*. |
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| [Ling-lite-Q5_K_L.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-Q5_K_L.gguf) | Q5_K_L | 12.91GB | false | Uses Q8_0 for embed and output weights. High quality, *recommended*. |
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| [Ling-lite-Q5_K_M.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-Q5_K_M.gguf) | Q5_K_M | 12.75GB | false | High quality, *recommended*. |
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| [Ling-lite-Q5_K_S.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-Q5_K_S.gguf) | Q5_K_S | 11.93GB | false | High quality, *recommended*. |
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| [Ling-lite-Q4_K_L.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-Q4_K_L.gguf) | Q4_K_L | 11.37GB | false | Uses Q8_0 for embed and output weights. Good quality, *recommended*. |
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| [Ling-lite-Q4_K_M.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-Q4_K_M.gguf) | Q4_K_M | 11.18GB | false | Good quality, default size for most use cases, *recommended*. |
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| [Ling-lite-Q4_1.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-Q4_1.gguf) | Q4_1 | 10.57GB | false | Legacy format, similar performance to Q4_K_S but with improved tokens/watt on Apple silicon. |
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| [Ling-lite-Q4_K_S.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-Q4_K_S.gguf) | Q4_K_S | 10.22GB | false | Slightly lower quality with more space savings, *recommended*. |
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| [Ling-lite-Q4_0.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-Q4_0.gguf) | Q4_0 | 9.57GB | false | Legacy format, offers online repacking for ARM and AVX CPU inference. |
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| [Ling-lite-IQ4_NL.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-IQ4_NL.gguf) | IQ4_NL | 9.54GB | false | Similar to IQ4_XS, but slightly larger. Offers online repacking for ARM CPU inference. |
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| [Ling-lite-Q3_K_XL.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-Q3_K_XL.gguf) | Q3_K_XL | 9.30GB | false | Uses Q8_0 for embed and output weights. Lower quality but usable, good for low RAM availability. |
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| [Ling-lite-IQ4_XS.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-IQ4_XS.gguf) | IQ4_XS | 9.19GB | false | Decent quality, smaller than Q4_K_S with similar performance, *recommended*. |
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| [Ling-lite-Q3_K_L.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-Q3_K_L.gguf) | Q3_K_L | 9.07GB | false | Lower quality but usable, good for low RAM availability. |
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| [Ling-lite-Q3_K_M.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-Q3_K_M.gguf) | Q3_K_M | 8.73GB | false | Low quality. |
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| [Ling-lite-IQ3_M.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-IQ3_M.gguf) | IQ3_M | 8.12GB | false | Medium-low quality, new method with decent performance comparable to Q3_K_M. |
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| [Ling-lite-Q3_K_S.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-Q3_K_S.gguf) | Q3_K_S | 8.03GB | false | Low quality, not recommended. |
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| [Ling-lite-IQ3_XS.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-IQ3_XS.gguf) | IQ3_XS | 7.65GB | false | Lower quality, new method with decent performance, slightly better than Q3_K_S. |
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| [Ling-lite-IQ3_XXS.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-IQ3_XXS.gguf) | IQ3_XXS | 7.47GB | false | Lower quality, new method with decent performance, comparable to Q3 quants. |
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| [Ling-lite-Q2_K_L.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-Q2_K_L.gguf) | Q2_K_L | 7.16GB | false | Uses Q8_0 for embed and output weights. Very low quality but surprisingly usable. |
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| [Ling-lite-Q2_K.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-Q2_K.gguf) | Q2_K | 6.91GB | false | Very low quality but surprisingly usable. |
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| [Ling-lite-IQ2_M.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-IQ2_M.gguf) | IQ2_M | 6.80GB | false | Relatively low quality, uses SOTA techniques to be surprisingly usable. |
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| [Ling-lite-IQ2_S.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-IQ2_S.gguf) | IQ2_S | 6.45GB | false | Low quality, uses SOTA techniques to be usable. |
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| [Ling-lite-IQ2_XS.gguf](https://huggingface.co/bartowski/inclusionAI_Ling-lite-GGUF/blob/main/inclusionAI_Ling-lite-IQ2_XS.gguf) | IQ2_XS | 6.41GB | false | Low quality, uses SOTA techniques to be usable. |
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## Embed/output weights
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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.
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## Downloading using huggingface-cli
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<details>
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<summary>Click to view download instructions</summary>
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First, make sure you have hugginface-cli installed:
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```
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pip install -U "huggingface_hub[cli]"
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```
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Then, you can target the specific file you want:
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```
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huggingface-cli download bartowski/inclusionAI_Ling-lite-GGUF --include "inclusionAI_Ling-lite-Q4_K_M.gguf" --local-dir ./
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```
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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:
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```
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huggingface-cli download bartowski/inclusionAI_Ling-lite-GGUF --include "inclusionAI_Ling-lite-Q8_0/*" --local-dir ./
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```
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You can either specify a new local-dir (inclusionAI_Ling-lite-Q8_0) or download them all in place (./)
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</details>
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## ARM/AVX information
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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.
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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.
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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.
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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.
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<details>
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<summary>Click to view Q4_0_X_X information (deprecated</summary>
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I'm keeping this section to show the potential theoretical uplift in performance from using the Q4_0 with online repacking.
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<details>
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<summary>Click to view benchmarks on an AVX2 system (EPYC7702)</summary>
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| model | size | params | backend | threads | test | t/s | % (vs Q4_0) |
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| ------------------------------ | ---------: | ---------: | ---------- | ------: | ------------: | -------------------: |-------------: |
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| qwen2 3B Q4_0 | 1.70 GiB | 3.09 B | CPU | 64 | pp512 | 204.03 ± 1.03 | 100% |
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| qwen2 3B Q4_0 | 1.70 GiB | 3.09 B | CPU | 64 | pp1024 | 282.92 ± 0.19 | 100% |
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| qwen2 3B Q4_0 | 1.70 GiB | 3.09 B | CPU | 64 | pp2048 | 259.49 ± 0.44 | 100% |
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| qwen2 3B Q4_0 | 1.70 GiB | 3.09 B | CPU | 64 | tg128 | 39.12 ± 0.27 | 100% |
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| qwen2 3B Q4_0 | 1.70 GiB | 3.09 B | CPU | 64 | tg256 | 39.31 ± 0.69 | 100% |
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| qwen2 3B Q4_0 | 1.70 GiB | 3.09 B | CPU | 64 | tg512 | 40.52 ± 0.03 | 100% |
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| qwen2 3B Q4_K_M | 1.79 GiB | 3.09 B | CPU | 64 | pp512 | 301.02 ± 1.74 | 147% |
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| qwen2 3B Q4_K_M | 1.79 GiB | 3.09 B | CPU | 64 | pp1024 | 287.23 ± 0.20 | 101% |
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| qwen2 3B Q4_K_M | 1.79 GiB | 3.09 B | CPU | 64 | pp2048 | 262.77 ± 1.81 | 101% |
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| qwen2 3B Q4_K_M | 1.79 GiB | 3.09 B | CPU | 64 | tg128 | 18.80 ± 0.99 | 48% |
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| qwen2 3B Q4_K_M | 1.79 GiB | 3.09 B | CPU | 64 | tg256 | 24.46 ± 3.04 | 83% |
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| qwen2 3B Q4_K_M | 1.79 GiB | 3.09 B | CPU | 64 | tg512 | 36.32 ± 3.59 | 90% |
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| qwen2 3B Q4_0_8_8 | 1.69 GiB | 3.09 B | CPU | 64 | pp512 | 271.71 ± 3.53 | 133% |
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| qwen2 3B Q4_0_8_8 | 1.69 GiB | 3.09 B | CPU | 64 | pp1024 | 279.86 ± 45.63 | 100% |
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| qwen2 3B Q4_0_8_8 | 1.69 GiB | 3.09 B | CPU | 64 | pp2048 | 320.77 ± 5.00 | 124% |
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| qwen2 3B Q4_0_8_8 | 1.69 GiB | 3.09 B | CPU | 64 | tg128 | 43.51 ± 0.05 | 111% |
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| qwen2 3B Q4_0_8_8 | 1.69 GiB | 3.09 B | CPU | 64 | tg256 | 43.35 ± 0.09 | 110% |
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| qwen2 3B Q4_0_8_8 | 1.69 GiB | 3.09 B | CPU | 64 | tg512 | 42.60 ± 0.31 | 105% |
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Q4_0_8_8 offers a nice bump to prompt processing and a small bump to text generation
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</details>
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</details>
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## Which file should I choose?
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<details>
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<summary>Click here for details</summary>
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A great write up with charts showing various performances is provided by Artefact2 [here](https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9)
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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.
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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.
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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.
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Next, you'll need to decide if you want to use an 'I-quant' or a 'K-quant'.
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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.
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If you want to get more into the weeds, you can check out this extremely useful feature chart:
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[llama.cpp feature matrix](https://github.com/ggerganov/llama.cpp/wiki/Feature-matrix)
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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.
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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.
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||||||
|
</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
|
||||||
1
configuration.json
Normal file
1
configuration.json
Normal file
@@ -0,0 +1 @@
|
|||||||
|
{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
|
||||||
3
inclusionAI_Ling-lite-IQ2_M.gguf
Normal file
3
inclusionAI_Ling-lite-IQ2_M.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:05b3e03a7d6f744e879edbaaa2be9eaf16138df10229efc99a1486439e5029aa
|
||||||
|
size 6796490304
|
||||||
3
inclusionAI_Ling-lite-IQ2_S.gguf
Normal file
3
inclusionAI_Ling-lite-IQ2_S.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:956a133953aef3279ee201a49f2a143d020d4d692cc614a5d2387ec9e6eedc08
|
||||||
|
size 6453982784
|
||||||
3
inclusionAI_Ling-lite-IQ2_XS.gguf
Normal file
3
inclusionAI_Ling-lite-IQ2_XS.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:400fcd2edcf19b1419ea78ec8fee8f8d24535fdac3f554fd414f063626fa3eaa
|
||||||
|
size 6410577472
|
||||||
3
inclusionAI_Ling-lite-IQ3_M.gguf
Normal file
3
inclusionAI_Ling-lite-IQ3_M.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:0958fda2a7ce34cf7ebcc810056b7813762d567bd79f74b2698b9f86721f5deb
|
||||||
|
size 8116766272
|
||||||
3
inclusionAI_Ling-lite-IQ3_XS.gguf
Normal file
3
inclusionAI_Ling-lite-IQ3_XS.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:3a04cc947d983fbd45fabd04680e9592fe8281202b81413f1da007cdb7f634da
|
||||||
|
size 7648097856
|
||||||
3
inclusionAI_Ling-lite-IQ3_XXS.gguf
Normal file
3
inclusionAI_Ling-lite-IQ3_XXS.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:73da2f60547b228629e15c3d256c515931ec9f72436f200b2033d73d31077cdb
|
||||||
|
size 7472059968
|
||||||
3
inclusionAI_Ling-lite-IQ4_NL.gguf
Normal file
3
inclusionAI_Ling-lite-IQ4_NL.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:49a41c800c3522544bcc57f939a58c46482233ed9e6ed893d552bba0234ecfbe
|
||||||
|
size 9539753536
|
||||||
3
inclusionAI_Ling-lite-IQ4_XS.gguf
Normal file
3
inclusionAI_Ling-lite-IQ4_XS.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:e81477bee23adfaa9184b06cfb1d8b2c80613ff1d9ebddb46e86ac9ec1bcea7e
|
||||||
|
size 9185302080
|
||||||
3
inclusionAI_Ling-lite-Q2_K.gguf
Normal file
3
inclusionAI_Ling-lite-Q2_K.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:60e8c55021acd6b93a45ac96ca51887198b0287b39e9d6865f35352720d86f63
|
||||||
|
size 6906025536
|
||||||
3
inclusionAI_Ling-lite-Q2_K_L.gguf
Normal file
3
inclusionAI_Ling-lite-Q2_K_L.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:14a4c3e8a9421c66ef689564f7821cadeab514aa3c3da2932dfb525a558987f5
|
||||||
|
size 7158953536
|
||||||
3
inclusionAI_Ling-lite-Q3_K_L.gguf
Normal file
3
inclusionAI_Ling-lite-Q3_K_L.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:066111709f2041604dd3f77317084058b94fad7ac0a768f3df37e692caa7f9a2
|
||||||
|
size 9074128448
|
||||||
3
inclusionAI_Ling-lite-Q3_K_M.gguf
Normal file
3
inclusionAI_Ling-lite-Q3_K_M.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:9efb32be1803e84bd40c96cd330e3da6215a4e5d85fb32845571d1760f8f9b26
|
||||||
|
size 8725149248
|
||||||
3
inclusionAI_Ling-lite-Q3_K_S.gguf
Normal file
3
inclusionAI_Ling-lite-Q3_K_S.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:a58cbfdcb28f822df339f1554c45a38372d8fa2c2948629418257023a695c923
|
||||||
|
size 8025765440
|
||||||
3
inclusionAI_Ling-lite-Q3_K_XL.gguf
Normal file
3
inclusionAI_Ling-lite-Q3_K_XL.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:10b3568b67c330ce88a3def05a285cba5e3ebc0dc9e8494da49bb4f8c84202b9
|
||||||
|
size 9300751936
|
||||||
3
inclusionAI_Ling-lite-Q4_0.gguf
Normal file
3
inclusionAI_Ling-lite-Q4_0.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:6072ade86e1c349fa6dca1ec472d150d19ef08519415b3a94768255f9e9650eb
|
||||||
|
size 9571767872
|
||||||
3
inclusionAI_Ling-lite-Q4_1.gguf
Normal file
3
inclusionAI_Ling-lite-Q4_1.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:62cc02cbcb2fca7fa2195b57a08bac7772158d412e85329db68d78983a08ad00
|
||||||
|
size 10569782848
|
||||||
3
inclusionAI_Ling-lite-Q4_K_L.gguf
Normal file
3
inclusionAI_Ling-lite-Q4_K_L.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:e75c3e5ddf9e6975b65cc4168ba54897f44f09442682c18ef1eb8dc3f022d4ed
|
||||||
|
size 11367716416
|
||||||
3
inclusionAI_Ling-lite-Q4_K_M.gguf
Normal file
3
inclusionAI_Ling-lite-Q4_K_M.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:cb9182f47d0e7ab90cc860da187b62c45c776a6912f697992e877027e67f9f6a
|
||||||
|
size 11175491136
|
||||||
3
inclusionAI_Ling-lite-Q4_K_S.gguf
Normal file
3
inclusionAI_Ling-lite-Q4_K_S.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:a032d9b667b2b1788820ba6c7069955b57933e361f1beea3caae482320612db8
|
||||||
|
size 10219296320
|
||||||
3
inclusionAI_Ling-lite-Q5_K_L.gguf
Normal file
3
inclusionAI_Ling-lite-Q5_K_L.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:22f9b886bbb302881f4d95ef803a3ba5a17366347821f33c9f61abe7fd9366bd
|
||||||
|
size 12906370624
|
||||||
3
inclusionAI_Ling-lite-Q5_K_M.gguf
Normal file
3
inclusionAI_Ling-lite-Q5_K_M.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:9e46b55358fded2f16fe91921125a8304da52205b493849f8f20408db0e3a6e9
|
||||||
|
size 12746520128
|
||||||
3
inclusionAI_Ling-lite-Q5_K_S.gguf
Normal file
3
inclusionAI_Ling-lite-Q5_K_S.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:c287b0ccd7344e45e7bc902220d3b1b927886f20b1cfae19ab86d2eed8cb9dd2
|
||||||
|
size 11926443584
|
||||||
3
inclusionAI_Ling-lite-Q6_K.gguf
Normal file
3
inclusionAI_Ling-lite-Q6_K.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:1df15126163b24315f7341630151c81ab995b41f5bd8dfd69ce8d1333fd19527
|
||||||
|
size 15051568704
|
||||||
3
inclusionAI_Ling-lite-Q6_K_L.gguf
Normal file
3
inclusionAI_Ling-lite-Q6_K_L.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:88d0ae5fe7ca0342c746e9ce58e40ffd274546e173b9e1f5d3fc96ca2e14aeb6
|
||||||
|
size 15177020992
|
||||||
3
inclusionAI_Ling-lite-Q8_0.gguf
Normal file
3
inclusionAI_Ling-lite-Q8_0.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:44d7db35040c2743a77a661a3669bbcdaeca4cebac0ea77a9944a92657b713f3
|
||||||
|
size 17868404288
|
||||||
3
inclusionAI_Ling-lite-bf16.gguf
Normal file
3
inclusionAI_Ling-lite-bf16.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:1db0a5120723673ffbbe3b5c16f8301048952b7811fe4330266ee9900541cfc3
|
||||||
|
size 33616704832
|
||||||
3
inclusionAI_Ling-lite.imatrix
Normal file
3
inclusionAI_Ling-lite.imatrix
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:86dd96de53314e381a5f368c42b14af217cf464d551ee0ba804668d07a1f08f0
|
||||||
|
size 41384946
|
||||||
Reference in New Issue
Block a user