初始化项目，由ModelHub XC社区提供模型
Model: bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF Source: Original Platform
This commit is contained in:
ModelHub XC
47
.gitattributes
vendored
Normal file
47
.gitattributes
vendored
Normal file
@@ -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
|
||||
176
README.md
Normal file
176
README.md
Normal file
@@ -0,0 +1,176 @@
|
||||
---
|
||||
quantized_by: bartowski
|
||||
pipeline_tag: text-generation
|
||||
language:
|
||||
- en
|
||||
base_model_relation: quantized
|
||||
license: cc-by-nc-4.0
|
||||
base_model: nvidia/Llama-3.1-8B-UltraLong-4M-Instruct
|
||||
---
|
||||
|
||||
## Llamacpp imatrix Quantizations of Llama-3.1-8B-UltraLong-4M-Instruct 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/b5074">b5074</a> for quantization.
|
||||
|
||||
Original model: https://huggingface.co/nvidia/Llama-3.1-8B-UltraLong-4M-Instruct
|
||||
|
||||
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
|
||||
|
||||
```
|
||||
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
|
||||
|
||||
Cutting Knowledge Date: December 2023
|
||||
Today Date: 26 Jul 2024
|
||||
|
||||
{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>
|
||||
|
||||
{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
|
||||
```
|
||||
|
||||
## Download a file (not the whole branch) from below:
|
||||
|
||||
| Filename | Quant type | File Size | Split | Description |
|
||||
| -------- | ---------- | --------- | ----- | ----------- |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-bf16.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-bf16.gguf) | bf16 | 16.08GB | false | Full BF16 weights. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-Q8_0.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q8_0.gguf) | Q8_0 | 8.55GB | false | Extremely high quality, generally unneeded but max available quant. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-Q6_K_L.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q6_K_L.gguf) | Q6_K_L | 6.86GB | false | Uses Q8_0 for embed and output weights. Very high quality, near perfect, *recommended*. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-Q6_K.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q6_K.gguf) | Q6_K | 6.60GB | false | Very high quality, near perfect, *recommended*. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-Q5_K_L.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q5_K_L.gguf) | Q5_K_L | 6.06GB | false | Uses Q8_0 for embed and output weights. High quality, *recommended*. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-Q5_K_M.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q5_K_M.gguf) | Q5_K_M | 5.74GB | false | High quality, *recommended*. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-Q5_K_S.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q5_K_S.gguf) | Q5_K_S | 5.60GB | false | High quality, *recommended*. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-Q4_K_L.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q4_K_L.gguf) | Q4_K_L | 5.32GB | false | Uses Q8_0 for embed and output weights. Good quality, *recommended*. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-Q4_1.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q4_1.gguf) | Q4_1 | 5.13GB | false | Legacy format, similar performance to Q4_K_S but with improved tokens/watt on Apple silicon. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-Q4_K_M.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q4_K_M.gguf) | Q4_K_M | 4.93GB | false | Good quality, default size for most use cases, *recommended*. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-Q3_K_XL.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q3_K_XL.gguf) | Q3_K_XL | 4.79GB | false | Uses Q8_0 for embed and output weights. Lower quality but usable, good for low RAM availability. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-Q4_K_S.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q4_K_S.gguf) | Q4_K_S | 4.70GB | false | Slightly lower quality with more space savings, *recommended*. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-Q4_0.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q4_0.gguf) | Q4_0 | 4.68GB | false | Legacy format, offers online repacking for ARM and AVX CPU inference. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-IQ4_NL.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-IQ4_NL.gguf) | IQ4_NL | 4.68GB | false | Similar to IQ4_XS, but slightly larger. Offers online repacking for ARM CPU inference. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-IQ4_XS.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-IQ4_XS.gguf) | IQ4_XS | 4.45GB | false | Decent quality, smaller than Q4_K_S with similar performance, *recommended*. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-Q3_K_L.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q3_K_L.gguf) | Q3_K_L | 4.33GB | false | Lower quality but usable, good for low RAM availability. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-Q3_K_M.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q3_K_M.gguf) | Q3_K_M | 4.02GB | false | Low quality. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-IQ3_M.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-IQ3_M.gguf) | IQ3_M | 3.79GB | false | Medium-low quality, new method with decent performance comparable to Q3_K_M. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-Q2_K_L.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q2_K_L.gguf) | Q2_K_L | 3.70GB | false | Uses Q8_0 for embed and output weights. Very low quality but surprisingly usable. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-Q3_K_S.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q3_K_S.gguf) | Q3_K_S | 3.67GB | false | Low quality, not recommended. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-IQ3_XS.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-IQ3_XS.gguf) | IQ3_XS | 3.52GB | false | Lower quality, new method with decent performance, slightly better than Q3_K_S. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-IQ3_XXS.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-IQ3_XXS.gguf) | IQ3_XXS | 3.28GB | false | Lower quality, new method with decent performance, comparable to Q3 quants. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-Q2_K.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q2_K.gguf) | Q2_K | 3.18GB | false | Very low quality but surprisingly usable. |
|
||||
| [Llama-3.1-8B-UltraLong-4M-Instruct-IQ2_M.gguf](https://huggingface.co/bartowski/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF/blob/main/nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-IQ2_M.gguf) | IQ2_M | 2.95GB | 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_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF --include "nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-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_Llama-3.1-8B-UltraLong-4M-Instruct-GGUF --include "nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q8_0/*" --local-dir ./
|
||||
```
|
||||
|
||||
You can either specify a new local-dir (nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-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
|
||||
1
configuration.json
Normal file
1
configuration.json
Normal file
@@ -0,0 +1 @@
|
||||
{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-IQ2_M.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-IQ2_M.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:2aba219bff258d0790170acabbe8f6685dddfed2065157576a21c3ff8a3cd6f7
|
||||
size 2951817824
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-IQ3_M.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-IQ3_M.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:76bb7d9ce3a629c820fa76e647a8dcf98fd9137352ae13db0a135eeb0395792f
|
||||
size 3788778080
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-IQ3_XS.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-IQ3_XS.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:a74f25af94914527e16677d4030f25e5041980f6eeb0d69b2ca4e81a76a91e68
|
||||
size 3522701920
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-IQ3_XXS.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-IQ3_XXS.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:bd166d3da190bdb1af2172a3e9fcc1e80c953c02912d95e986845a9f1cb43162
|
||||
size 3278449248
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-IQ4_NL.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-IQ4_NL.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:c8c73e78fd605355ec0a8a00f1f9dff22b281ca27b607810a190160f5e55964c
|
||||
size 4682361440
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-IQ4_XS.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-IQ4_XS.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:198300a1e7fa6831ba945785f7b9a29797c4dbc92c1afdc3fb2cf29215129646
|
||||
size 4451936864
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q2_K.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q2_K.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:f2b388246613ff478b50c79ce387caf967d1f5003874ff5de456a5868123fd6a
|
||||
size 3182766688
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q2_K_L.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q2_K_L.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:c2ccffca425013c1eb421948379b529580c9b525bcb531d00f899b6e44ee328c
|
||||
size 3698862688
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q3_K_L.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q3_K_L.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:dd6c3584f8a2fab5dec22b4883344035eb698dcf57cc61a38a9a9db4fcfe8916
|
||||
size 4325911136
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q3_K_M.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q3_K_M.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:6a8bc108aacbf549799d0e8d1283a9aba574c185fdaa097b716060d15195a1dc
|
||||
size 4022872672
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q3_K_S.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q3_K_S.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:199a2f8a3668be8ee084635cdd07bd69819088c9245d7b243bf25b141a93fd51
|
||||
size 3668453984
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q3_K_XL.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q3_K_XL.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:fe835734bac2729465937e8c0fa1969b2bf6a790f74deeb97fba48512cfac4f7
|
||||
size 4788333152
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q4_0.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q4_0.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:3e15f03c8e8cca9b173845ea4b07baa4fcb7f2262a79bbec7a552d3d015f8d6f
|
||||
size 4680264288
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q4_1.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q4_1.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:3caae6af712fae5bb72b6ed0596f47cc39cf820e30039412393961699d5e59d6
|
||||
size 5134821984
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q4_K_L.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q4_K_L.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:dd6939224cec4fa41de92ffd542d27a2c7d543ab505495113d6f5c22b52ddc6b
|
||||
size 5317339744
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q4_K_M.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q4_K_M.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:c503c77c6d8cc4be53ce7cddb756cb571862f0422594c17e58a75d7be9f00907
|
||||
size 4925106784
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q4_K_S.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q4_K_S.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:82f7190370b583e04e3b9b27cbd49358b603e4b208cb02a52a245c06104f0945
|
||||
size 4697041504
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q5_K_L.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q5_K_L.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:0b324904b1ab6ea1dcbdda63c08cb2fad734f0e13e9706337b19fc7ae6f367c8
|
||||
size 6063925856
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q5_K_M.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q5_K_M.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:1971cc65f150c50243fcb135998e0d19b7c7de1c1b1a6051d6b0edc65635b1b3
|
||||
size 5737753184
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q5_K_S.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q5_K_S.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:eb4ec12fefd6c28ef5d9a15e626b5614434afcb299be7e4082f7433ff8887dae
|
||||
size 5604059744
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q6_K.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q6_K.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:8bff6498e3cc26181a2957c2d7d961aa350fedb3efa97ded8c03f72f06ba26a2
|
||||
size 6601189984
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q6_K_L.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q6_K_L.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:1e0f3eb1347545077ece2455657aed30bf9c177f6e3960ec6afd311e8f2a3d51
|
||||
size 6857173600
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q8_0.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-Q8_0.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:f74fb882c226d6d774f0a91a77cce46285b38d2a3fa453859045083c6748e51d
|
||||
size 8547478112
|
||||
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-bf16.gguf
Normal file
3
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct-bf16.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:88dc0d70ea88b34b10adf7a89a9cf69a7c8c1ef8eac8c35086e404da3ddfeaa5
|
||||
size 16081496352
|
||||
BIN
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct.imatrix
Normal file
BIN
nvidia_Llama-3.1-8B-UltraLong-4M-Instruct.imatrix
Normal file
Binary file not shown.
Reference in New Issue
Block a user