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Model: legraphista/Qwen2-1.5B-Instruct-IMat-GGUF Source: Original Platform
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---
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base_model: Qwen/Qwen2-1.5B-Instruct
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inference: false
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language:
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- en
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library_name: gguf
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license: apache-2.0
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pipeline_tag: text-generation
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quantized_by: legraphista
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tags:
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- chat
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- quantized
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- GGUF
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- imatrix
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- quantization
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- imat
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- imatrix
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- static
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- 16bit
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- 8bit
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- 6bit
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- 5bit
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- 4bit
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- 3bit
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- 2bit
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- 1bit
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---
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# Qwen2-1.5B-Instruct-IMat-GGUF
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_Llama.cpp imatrix quantization of Qwen/Qwen2-1.5B-Instruct_
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Original Model: [Qwen/Qwen2-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2-1.5B-Instruct)
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Original dtype: `BF16` (`bfloat16`)
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Quantized by: llama.cpp [b3091](https://github.com/ggerganov/llama.cpp/releases/tag/b3091)
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IMatrix dataset: [here](https://gist.githubusercontent.com/bartowski1182/eb213dccb3571f863da82e99418f81e8/raw/b2869d80f5c16fd7082594248e80144677736635/calibration_datav3.txt)
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- [Files](#files)
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- [IMatrix](#imatrix)
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- [Common Quants](#common-quants)
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- [All Quants](#all-quants)
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- [Downloading using huggingface-cli](#downloading-using-huggingface-cli)
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- [Inference](#inference)
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- [Simple chat template](#simple-chat-template)
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- [Chat template with system prompt](#chat-template-with-system-prompt)
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- [Llama.cpp](#llama-cpp)
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- [FAQ](#faq)
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- [Why is the IMatrix not applied everywhere?](#why-is-the-imatrix-not-applied-everywhere)
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- [How do I merge a split GGUF?](#how-do-i-merge-a-split-gguf)
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---
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## Files
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### IMatrix
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Status: ✅ Available
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Link: [here](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/imatrix.dat)
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### Common Quants
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| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
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| -------- | ---------- | --------- | ------ | ------------ | -------- |
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| [Qwen2-1.5B-Instruct.Q8_0.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.Q8_0.gguf) | Q8_0 | 1.65GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.Q6_K.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.Q6_K.gguf) | Q6_K | 1.27GB | ✅ Available | ⚪ Static | 📦 No
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| [Qwen2-1.5B-Instruct.Q4_K.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.Q4_K.gguf) | Q4_K | 986.05MB | ✅ Available | 🟢 IMatrix | 📦 No
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| [Qwen2-1.5B-Instruct.Q3_K.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.Q3_K.gguf) | Q3_K | 824.18MB | ✅ Available | 🟢 IMatrix | 📦 No
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| [Qwen2-1.5B-Instruct.Q2_K.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.Q2_K.gguf) | Q2_K | 676.30MB | ✅ Available | 🟢 IMatrix | 📦 No
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### All Quants
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| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
|
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| -------- | ---------- | --------- | ------ | ------------ | -------- |
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| [Qwen2-1.5B-Instruct.BF16.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.BF16.gguf) | BF16 | 3.09GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.FP16.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.FP16.gguf) | F16 | 3.09GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.Q8_0.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.Q8_0.gguf) | Q8_0 | 1.65GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.Q6_K.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.Q6_K.gguf) | Q6_K | 1.27GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.Q5_K.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.Q5_K.gguf) | Q5_K | 1.13GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.Q5_K_S.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.Q5_K_S.gguf) | Q5_K_S | 1.10GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.Q4_K.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.Q4_K.gguf) | Q4_K | 986.05MB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.Q4_K_S.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.Q4_K_S.gguf) | Q4_K_S | 940.31MB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.IQ4_NL.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.IQ4_NL.gguf) | IQ4_NL | 936.33MB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.IQ4_XS.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.IQ4_XS.gguf) | IQ4_XS | 895.73MB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.Q3_K.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.Q3_K.gguf) | Q3_K | 824.18MB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.Q3_K_L.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.Q3_K_L.gguf) | Q3_K_L | 880.16MB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.Q3_K_S.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.Q3_K_S.gguf) | Q3_K_S | 760.94MB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.IQ3_M.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.IQ3_M.gguf) | IQ3_M | 776.66MB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.IQ3_S.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.IQ3_S.gguf) | IQ3_S | 762.40MB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.IQ3_XS.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.IQ3_XS.gguf) | IQ3_XS | 731.70MB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.IQ3_XXS.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.IQ3_XXS.gguf) | IQ3_XXS | 668.79MB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.Q2_K.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.Q2_K.gguf) | Q2_K | 676.30MB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.Q2_K_S.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.Q2_K_S.gguf) | Q2_K_S | 640.13MB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.IQ2_M.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.IQ2_M.gguf) | IQ2_M | 601.05MB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.IQ2_S.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.IQ2_S.gguf) | IQ2_S | 563.81MB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.IQ2_XS.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.IQ2_XS.gguf) | IQ2_XS | 550.32MB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.IQ2_XXS.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.IQ2_XXS.gguf) | IQ2_XXS | 511.01MB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.IQ1_M.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.IQ1_M.gguf) | IQ1_M | 464.46MB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Qwen2-1.5B-Instruct.IQ1_S.gguf](https://huggingface.co/legraphista/Qwen2-1.5B-Instruct-IMat-GGUF/blob/main/Qwen2-1.5B-Instruct.IQ1_S.gguf) | IQ1_S | 436.52MB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
|
||||
|
||||
## Downloading using huggingface-cli
|
||||
If you do not have hugginface-cli installed:
|
||||
```
|
||||
pip install -U "huggingface_hub[cli]"
|
||||
```
|
||||
Download the specific file you want:
|
||||
```
|
||||
huggingface-cli download legraphista/Qwen2-1.5B-Instruct-IMat-GGUF --include "Qwen2-1.5B-Instruct.Q8_0.gguf" --local-dir ./
|
||||
```
|
||||
If the model file is big, it has been split into multiple files. In order to download them all to a local folder, run:
|
||||
```
|
||||
huggingface-cli download legraphista/Qwen2-1.5B-Instruct-IMat-GGUF --include "Qwen2-1.5B-Instruct.Q8_0/*" --local-dir ./
|
||||
# see FAQ for merging GGUF's
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Inference
|
||||
|
||||
### Simple chat template
|
||||
```
|
||||
<|im_start|>system
|
||||
You are a helpful assistant.<|im_end|>
|
||||
<|im_start|>user
|
||||
{user_prompt}<|im_end|>
|
||||
<|im_start|>assistant
|
||||
{assistant_response}<|im_end|>
|
||||
<|im_start|>user
|
||||
{next_user_prompt}<|im_end|>
|
||||
|
||||
```
|
||||
|
||||
### Chat template with system prompt
|
||||
```
|
||||
<|im_start|>system
|
||||
{system_prompt}<|im_end|>
|
||||
<|im_start|>user
|
||||
{user_prompt}<|im_end|>
|
||||
<|im_start|>assistant
|
||||
{assistant_response}<|im_end|>
|
||||
<|im_start|>user
|
||||
{next_user_prompt}<|im_end|>
|
||||
|
||||
```
|
||||
|
||||
### Llama.cpp
|
||||
```
|
||||
llama.cpp/main -m Qwen2-1.5B-Instruct.Q8_0.gguf --color -i -p "prompt here (according to the chat template)"
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## FAQ
|
||||
|
||||
### Why is the IMatrix not applied everywhere?
|
||||
According to [this investigation](https://www.reddit.com/r/LocalLLaMA/comments/1993iro/ggufs_quants_can_punch_above_their_weights_now/), it appears that lower quantizations are the only ones that benefit from the imatrix input (as per hellaswag results).
|
||||
|
||||
### How do I merge a split GGUF?
|
||||
1. Make sure you have `gguf-split` available
|
||||
- To get hold of `gguf-split`, navigate to https://github.com/ggerganov/llama.cpp/releases
|
||||
- Download the appropriate zip for your system from the latest release
|
||||
- Unzip the archive and you should be able to find `gguf-split`
|
||||
2. Locate your GGUF chunks folder (ex: `Qwen2-1.5B-Instruct.Q8_0`)
|
||||
3. Run `gguf-split --merge Qwen2-1.5B-Instruct.Q8_0/Qwen2-1.5B-Instruct.Q8_0-00001-of-XXXXX.gguf Qwen2-1.5B-Instruct.Q8_0.gguf`
|
||||
- Make sure to point `gguf-split` to the first chunk of the split.
|
||||
|
||||
---
|
||||
|
||||
Got a suggestion? Ping me [@legraphista](https://x.com/legraphista)!
|
||||
3
imatrix.dat
Normal file
3
imatrix.dat
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:288627fe02e1a3fe50de229af3dc76fc176f311669e2a228f77567656addec53
|
||||
size 2042223
|
||||
2482
imatrix.dataset
Normal file
2482
imatrix.dataset
Normal file
File diff suppressed because one or more lines are too long
137
imatrix.log
Normal file
137
imatrix.log
Normal file
@@ -0,0 +1,137 @@
|
||||
main: build = 3086 (554c247c)
|
||||
main: built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
|
||||
main: seed = 1717699094
|
||||
llama_model_loader: loaded meta data with 21 key-value pairs and 338 tensors from Qwen2-1.5B-Instruct-IMat-GGUF/Qwen2-1.5B-Instruct.gguf (version GGUF V3 (latest))
|
||||
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
|
||||
llama_model_loader: - kv 0: general.architecture str = qwen2
|
||||
llama_model_loader: - kv 1: general.name str = Qwen2-1.5B-Instruct
|
||||
llama_model_loader: - kv 2: qwen2.block_count u32 = 28
|
||||
llama_model_loader: - kv 3: qwen2.context_length u32 = 32768
|
||||
llama_model_loader: - kv 4: qwen2.embedding_length u32 = 1536
|
||||
llama_model_loader: - kv 5: qwen2.feed_forward_length u32 = 8960
|
||||
llama_model_loader: - kv 6: qwen2.attention.head_count u32 = 12
|
||||
llama_model_loader: - kv 7: qwen2.attention.head_count_kv u32 = 2
|
||||
llama_model_loader: - kv 8: qwen2.rope.freq_base f32 = 1000000.000000
|
||||
llama_model_loader: - kv 9: qwen2.attention.layer_norm_rms_epsilon f32 = 0.000001
|
||||
llama_model_loader: - kv 10: general.file_type u32 = 0
|
||||
llama_model_loader: - kv 11: tokenizer.ggml.model str = gpt2
|
||||
llama_model_loader: - kv 12: tokenizer.ggml.pre str = qwen2
|
||||
llama_model_loader: - kv 13: tokenizer.ggml.tokens arr[str,151936] = ["!", "\"", "#", "$", "%", "&", "'", ...
|
||||
llama_model_loader: - kv 14: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
|
||||
llama_model_loader: - kv 15: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
|
||||
llama_model_loader: - kv 16: tokenizer.ggml.eos_token_id u32 = 151645
|
||||
llama_model_loader: - kv 17: tokenizer.ggml.padding_token_id u32 = 151643
|
||||
llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32 = 151643
|
||||
llama_model_loader: - kv 19: tokenizer.chat_template str = {% for message in messages %}{% if lo...
|
||||
llama_model_loader: - kv 20: general.quantization_version u32 = 2
|
||||
llama_model_loader: - type f32: 338 tensors
|
||||
llm_load_vocab: special tokens cache size = 293
|
||||
llm_load_vocab: token to piece cache size = 0.9338 MB
|
||||
llm_load_print_meta: format = GGUF V3 (latest)
|
||||
llm_load_print_meta: arch = qwen2
|
||||
llm_load_print_meta: vocab type = BPE
|
||||
llm_load_print_meta: n_vocab = 151936
|
||||
llm_load_print_meta: n_merges = 151387
|
||||
llm_load_print_meta: n_ctx_train = 32768
|
||||
llm_load_print_meta: n_embd = 1536
|
||||
llm_load_print_meta: n_head = 12
|
||||
llm_load_print_meta: n_head_kv = 2
|
||||
llm_load_print_meta: n_layer = 28
|
||||
llm_load_print_meta: n_rot = 128
|
||||
llm_load_print_meta: n_embd_head_k = 128
|
||||
llm_load_print_meta: n_embd_head_v = 128
|
||||
llm_load_print_meta: n_gqa = 6
|
||||
llm_load_print_meta: n_embd_k_gqa = 256
|
||||
llm_load_print_meta: n_embd_v_gqa = 256
|
||||
llm_load_print_meta: f_norm_eps = 0.0e+00
|
||||
llm_load_print_meta: f_norm_rms_eps = 1.0e-06
|
||||
llm_load_print_meta: f_clamp_kqv = 0.0e+00
|
||||
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
|
||||
llm_load_print_meta: f_logit_scale = 0.0e+00
|
||||
llm_load_print_meta: n_ff = 8960
|
||||
llm_load_print_meta: n_expert = 0
|
||||
llm_load_print_meta: n_expert_used = 0
|
||||
llm_load_print_meta: causal attn = 1
|
||||
llm_load_print_meta: pooling type = 0
|
||||
llm_load_print_meta: rope type = 2
|
||||
llm_load_print_meta: rope scaling = linear
|
||||
llm_load_print_meta: freq_base_train = 1000000.0
|
||||
llm_load_print_meta: freq_scale_train = 1
|
||||
llm_load_print_meta: n_yarn_orig_ctx = 32768
|
||||
llm_load_print_meta: rope_finetuned = unknown
|
||||
llm_load_print_meta: ssm_d_conv = 0
|
||||
llm_load_print_meta: ssm_d_inner = 0
|
||||
llm_load_print_meta: ssm_d_state = 0
|
||||
llm_load_print_meta: ssm_dt_rank = 0
|
||||
llm_load_print_meta: model type = ?B
|
||||
llm_load_print_meta: model ftype = all F32
|
||||
llm_load_print_meta: model params = 1.54 B
|
||||
llm_load_print_meta: model size = 5.75 GiB (32.00 BPW)
|
||||
llm_load_print_meta: general.name = Qwen2-1.5B-Instruct
|
||||
llm_load_print_meta: BOS token = 151643 '<|endoftext|>'
|
||||
llm_load_print_meta: EOS token = 151645 '<|im_end|>'
|
||||
llm_load_print_meta: PAD token = 151643 '<|endoftext|>'
|
||||
llm_load_print_meta: LF token = 148848 'ÄĬ'
|
||||
llm_load_print_meta: EOT token = 151645 '<|im_end|>'
|
||||
ggml_cuda_init: failed to initialize CUDA: no CUDA-capable device is detected
|
||||
llm_load_tensors: ggml ctx size = 0.16 MiB
|
||||
llm_load_tensors: offloading 0 repeating layers to GPU
|
||||
llm_load_tensors: offloaded 0/29 layers to GPU
|
||||
llm_load_tensors: CPU buffer size = 5888.80 MiB
|
||||
............................................................................
|
||||
llama_new_context_with_model: n_ctx = 512
|
||||
llama_new_context_with_model: n_batch = 512
|
||||
llama_new_context_with_model: n_ubatch = 512
|
||||
llama_new_context_with_model: flash_attn = 0
|
||||
llama_new_context_with_model: freq_base = 1000000.0
|
||||
llama_new_context_with_model: freq_scale = 1
|
||||
ggml_cuda_host_malloc: failed to allocate 14.00 MiB of pinned memory: no CUDA-capable device is detected
|
||||
llama_kv_cache_init: CPU KV buffer size = 14.00 MiB
|
||||
llama_new_context_with_model: KV self size = 14.00 MiB, K (f16): 7.00 MiB, V (f16): 7.00 MiB
|
||||
ggml_cuda_host_malloc: failed to allocate 0.58 MiB of pinned memory: no CUDA-capable device is detected
|
||||
llama_new_context_with_model: CPU output buffer size = 0.58 MiB
|
||||
ggml_cuda_host_malloc: failed to allocate 299.75 MiB of pinned memory: no CUDA-capable device is detected
|
||||
llama_new_context_with_model: CUDA_Host compute buffer size = 299.75 MiB
|
||||
llama_new_context_with_model: graph nodes = 986
|
||||
llama_new_context_with_model: graph splits = 1
|
||||
|
||||
system_info: n_threads = 25 / 32 | AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 1 | AVX512_VBMI = 1 | AVX512_VNNI = 1 | AVX512_BF16 = 1 | FMA = 1 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 |
|
||||
compute_imatrix: tokenizing the input ..
|
||||
compute_imatrix: tokenization took 186.265 ms
|
||||
compute_imatrix: computing over 128 chunks with batch_size 512
|
||||
ggml_cuda_host_malloc: failed to allocate 296.75 MiB of pinned memory: no CUDA-capable device is detected
|
||||
compute_imatrix: 2.29 seconds per pass - ETA 4.87 minutes
|
||||
[1]7.1794,[2]5.3199,[3]5.0981,[4]5.9752,[5]5.7835,[6]5.2552,[7]5.7864,[8]6.0622,[9]6.6684,
|
||||
save_imatrix: stored collected data after 10 chunks in Qwen2-1.5B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[10]6.3131,[11]6.1593,[12]6.6159,[13]7.3010,[14]7.5457,[15]8.1246,[16]8.5172,[17]8.6254,[18]9.1089,[19]8.7735,
|
||||
save_imatrix: stored collected data after 20 chunks in Qwen2-1.5B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[20]8.8735,[21]8.9815,[22]8.9399,[23]8.8281,[24]9.1095,[25]9.2579,[26]9.1932,[27]9.4461,[28]9.6855,[29]9.9663,
|
||||
save_imatrix: stored collected data after 30 chunks in Qwen2-1.5B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[30]9.8592,[31]9.4931,[32]9.0860,[33]8.8363,[34]8.6863,[35]8.5233,[36]8.5521,[37]8.6577,[38]8.7731,[39]8.8116,
|
||||
save_imatrix: stored collected data after 40 chunks in Qwen2-1.5B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[40]8.9578,[41]9.0102,[42]9.3965,[43]9.7582,[44]10.0824,[45]10.3412,[46]10.4822,[47]10.2945,[48]10.3357,[49]10.4302,
|
||||
save_imatrix: stored collected data after 50 chunks in Qwen2-1.5B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[50]10.4853,[51]10.3433,[52]10.4344,[53]10.6284,[54]10.7379,[55]10.8603,[56]10.8917,[57]10.9144,[58]10.9545,[59]10.9503,
|
||||
save_imatrix: stored collected data after 60 chunks in Qwen2-1.5B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[60]10.9594,[61]10.8658,[62]10.8120,[63]10.8641,[64]10.9371,[65]10.8705,[66]10.8679,[67]10.8664,[68]10.7898,[69]10.7536,
|
||||
save_imatrix: stored collected data after 70 chunks in Qwen2-1.5B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[70]10.7331,[71]10.6848,[72]10.6564,[73]10.6672,[74]10.5752,[75]10.4921,[76]10.4074,[77]10.3769,[78]10.3653,[79]10.3378,
|
||||
save_imatrix: stored collected data after 80 chunks in Qwen2-1.5B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[80]10.2752,[81]10.2969,[82]10.2784,[83]10.2086,[84]10.2478,[85]10.2686,[86]10.2003,[87]10.1497,[88]10.1223,[89]10.1420,
|
||||
save_imatrix: stored collected data after 90 chunks in Qwen2-1.5B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[90]10.1469,[91]10.1228,[92]10.0276,[93]9.9300,[94]9.8304,[95]9.7334,[96]9.6549,[97]9.5611,[98]9.4757,[99]9.4329,
|
||||
save_imatrix: stored collected data after 100 chunks in Qwen2-1.5B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[100]9.4376,[101]9.4618,[102]9.5825,[103]9.6851,[104]9.7748,[105]9.9226,[106]10.0201,[107]10.0571,[108]10.0244,[109]10.0150,
|
||||
save_imatrix: stored collected data after 110 chunks in Qwen2-1.5B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[110]10.0121,[111]9.9965,[112]9.9513,[113]9.9758,[114]10.0245,[115]10.0159,[116]10.0171,[117]10.0315,[118]10.0678,[119]10.0564,
|
||||
save_imatrix: stored collected data after 120 chunks in Qwen2-1.5B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[120]10.0484,[121]10.0499,[122]10.0063,[123]10.0592,[124]10.1353,[125]10.1928,[126]10.2749,[127]10.3396,[128]10.4061,
|
||||
save_imatrix: stored collected data after 128 chunks in Qwen2-1.5B-Instruct-IMat-GGUF/imatrix.dat
|
||||
|
||||
llama_print_timings: load time = 2730.80 ms
|
||||
llama_print_timings: sample time = 0.00 ms / 1 runs ( 0.00 ms per token, inf tokens per second)
|
||||
llama_print_timings: prompt eval time = 1324946.47 ms / 65536 tokens ( 20.22 ms per token, 49.46 tokens per second)
|
||||
llama_print_timings: eval time = 0.00 ms / 1 runs ( 0.00 ms per token, inf tokens per second)
|
||||
llama_print_timings: total time = 1327865.09 ms / 65537 tokens
|
||||
|
||||
Final estimate: PPL = 10.4061 +/- 0.15435
|
||||
Reference in New Issue
Block a user