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Model: legraphista/openchat-3.6-8b-20240522-IMat-GGUF Source: Original Platform
2026-09-08 13:28:16 +08:00
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+openchat-3.6-8b-20240522.Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
+openchat-3.6-8b-20240522.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
+openchat-3.6-8b-20240522.Q5_K.gguf filter=lfs diff=lfs merge=lfs -text
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+openchat-3.6-8b-20240522.BF16.gguf filter=lfs diff=lfs merge=lfs -text
+imatrix.dat filter=lfs diff=lfs merge=lfs -text
+openchat-3.6-8b-20240522.Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
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+openchat-3.6-8b-20240522.Q4_K.gguf filter=lfs diff=lfs merge=lfs -text
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+openchat-3.6-8b-20240522.IQ2_XS.gguf filter=lfs diff=lfs merge=lfs -text
+openchat-3.6-8b-20240522.IQ2_XXS.gguf filter=lfs diff=lfs merge=lfs -text
+openchat-3.6-8b-20240522.IQ1_M.gguf filter=lfs diff=lfs merge=lfs -text
+openchat-3.6-8b-20240522.IQ1_S.gguf filter=lfs diff=lfs merge=lfs -text
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+---
+base_model: openchat/openchat-3.6-8b-20240522
+inference: false
+library_name: gguf
+license: llama3
+pipeline_tag: text-generation
+quantized_by: legraphista
+tags:
+- quantized
+- GGUF
+- imatrix
+- quantization
+- imat
+- imatrix
+- static
+---
+
+# openchat-3.6-8b-20240522-IMat-GGUF
+_Llama.cpp imatrix quantization of openchat/openchat-3.6-8b-20240522_
+
+Original Model: [openchat/openchat-3.6-8b-20240522](https://huggingface.co/openchat/openchat-3.6-8b-20240522)  
+Original dtype: `BF16` (`bfloat16`)  
+Quantized by: llama.cpp [b3006](https://github.com/ggerganov/llama.cpp/releases/tag/b3006)  
+IMatrix dataset: [here](https://gist.githubusercontent.com/legraphista/d6d93f1a254bcfc58e0af3777eaec41e/raw/d380e7002cea4a51c33fffd47db851942754e7cc/imatrix.calibration.medium.raw)  
+
+- [openchat-3.6-8b-20240522-IMat-GGUF](#openchat-3-6-8b-20240522-imat-gguf)
+    - [Files](#files)
+        - [IMatrix](#imatrix)
+        - [Common Quants](#common-quants)
+        - [All Quants](#all-quants)
+    - [Downloading using huggingface-cli](#downloading-using-huggingface-cli)
+    - [Inference](#inference)
+        - [Simple chat template](#simple-chat-template)
+        - [Chat template with system prompt](#chat-template-with-system-prompt)
+        - [Llama.cpp](#llama-cpp)
+    - [FAQ](#faq)
+        - [Why is the IMatrix not applied everywhere?](#why-is-the-imatrix-not-applied-everywhere)
+        - [How do I merge a split GGUF?](#how-do-i-merge-a-split-gguf)
+
+---
+
+## Files
+
+### IMatrix
+Status: ✅ Available  
+Link: [here](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/imatrix.dat) 
+
+### Common Quants
+| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
+| -------- | ---------- | --------- | ------ | ------------ | -------- |
+| [openchat-3.6-8b-20240522.Q8_0.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.Q8_0.gguf) | Q8_0 | 8.54GB | ✅ Available | ⚪ Static | 📦 No
+| [openchat-3.6-8b-20240522.Q6_K.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.Q6_K.gguf) | Q6_K | 6.60GB | ✅ Available | ⚪ Static | 📦 No
+| [openchat-3.6-8b-20240522.Q4_K.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.Q4_K.gguf) | Q4_K | 4.92GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [openchat-3.6-8b-20240522.Q3_K.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.Q3_K.gguf) | Q3_K | 4.02GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [openchat-3.6-8b-20240522.Q2_K.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.Q2_K.gguf) | Q2_K | 3.18GB | ✅ Available | 🟢 IMatrix | 📦 No
+
+
+### All Quants
+| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
+| -------- | ---------- | --------- | ------ | ------------ | -------- |
+| [openchat-3.6-8b-20240522.FP16.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.FP16.gguf) | F16 | 16.07GB | ✅ Available | ⚪ Static | 📦 No
+| [openchat-3.6-8b-20240522.BF16.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.BF16.gguf) | BF16 | 16.07GB | ✅ Available | ⚪ Static | 📦 No
+| [openchat-3.6-8b-20240522.Q5_K.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.Q5_K.gguf) | Q5_K | 5.73GB | ✅ Available | ⚪ Static | 📦 No
+| [openchat-3.6-8b-20240522.Q5_K_S.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.Q5_K_S.gguf) | Q5_K_S | 5.60GB | ✅ Available | ⚪ Static | 📦 No
+| [openchat-3.6-8b-20240522.Q4_K_S.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.Q4_K_S.gguf) | Q4_K_S | 4.69GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [openchat-3.6-8b-20240522.Q3_K_L.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.Q3_K_L.gguf) | Q3_K_L | 4.32GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [openchat-3.6-8b-20240522.Q3_K_S.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.Q3_K_S.gguf) | Q3_K_S | 3.66GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [openchat-3.6-8b-20240522.Q2_K_S.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.Q2_K_S.gguf) | Q2_K_S | 2.99GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [openchat-3.6-8b-20240522.IQ4_NL.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.IQ4_NL.gguf) | IQ4_NL | 4.68GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [openchat-3.6-8b-20240522.IQ4_XS.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.IQ4_XS.gguf) | IQ4_XS | 4.45GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [openchat-3.6-8b-20240522.IQ3_M.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.IQ3_M.gguf) | IQ3_M | 3.78GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [openchat-3.6-8b-20240522.IQ3_S.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.IQ3_S.gguf) | IQ3_S | 3.68GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [openchat-3.6-8b-20240522.IQ3_XS.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.IQ3_XS.gguf) | IQ3_XS | 3.52GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [openchat-3.6-8b-20240522.IQ3_XXS.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.IQ3_XXS.gguf) | IQ3_XXS | 3.27GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [openchat-3.6-8b-20240522.IQ2_M.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.IQ2_M.gguf) | IQ2_M | 2.95GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [openchat-3.6-8b-20240522.IQ2_S.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.IQ2_S.gguf) | IQ2_S | 2.76GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [openchat-3.6-8b-20240522.IQ2_XS.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.IQ2_XS.gguf) | IQ2_XS | 2.61GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [openchat-3.6-8b-20240522.IQ2_XXS.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.IQ2_XXS.gguf) | IQ2_XXS | 2.40GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [openchat-3.6-8b-20240522.IQ1_M.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.IQ1_M.gguf) | IQ1_M | 2.16GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [openchat-3.6-8b-20240522.IQ1_S.gguf](https://huggingface.co/legraphista/openchat-3.6-8b-20240522-IMat-GGUF/blob/main/openchat-3.6-8b-20240522.IQ1_S.gguf) | IQ1_S | 2.02GB | ✅ 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/openchat-3.6-8b-20240522-IMat-GGUF --include "openchat-3.6-8b-20240522.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/openchat-3.6-8b-20240522-IMat-GGUF --include "openchat-3.6-8b-20240522.Q8_0/*" --local-dir openchat-3.6-8b-20240522.Q8_0
+# see FAQ for merging GGUF's
+```
+
+---
+
+## Inference
+
+### Simple chat template
+```
+<|begin_of_text|><|start_header_id|>GPT4 Correct User<|end_header_id|>
+
+Can you provide ways to eat combinations of bananas and dragonfruits?<|eot_id|><|start_header_id|>GPT4 Correct Assistant<|end_header_id|>
+
+Sure! Here are some ways to eat bananas and dragonfruits together:
+ 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey.
+ 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey.<|eot_id|><|start_header_id|>GPT4 Correct User<|end_header_id|>
+
+What about solving an 2x + 3 = 7 equation?<|eot_id|>
+```
+
+### Chat template with system prompt
+```
+<|begin_of_text|><|start_header_id|>System<|end_header_id|>
+
+You are a helpful AI.<|eot_id|><|start_header_id|>GPT4 Correct User<|end_header_id|>
+
+Can you provide ways to eat combinations of bananas and dragonfruits?<|eot_id|><|start_header_id|>GPT4 Correct Assistant<|end_header_id|>
+
+Sure! Here are some ways to eat bananas and dragonfruits together:
+ 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey.
+ 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey.<|eot_id|><|start_header_id|>GPT4 Correct User<|end_header_id|>
+
+What about solving an 2x + 3 = 7 equation?<|eot_id|>
+```
+
+### Llama.cpp
+```
+llama.cpp/main -m openchat-3.6-8b-20240522.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: `openchat-3.6-8b-20240522.Q8_0`)
+3. Run `gguf-split --merge openchat-3.6-8b-20240522.Q8_0/openchat-3.6-8b-20240522.Q8_0-00001-of-XXXXX.gguf openchat-3.6-8b-20240522.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)!
--- a/imatrix.dat
+++ b/imatrix.dat
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5c9ce18469f85eb75664620bc2cfdfee61bd9e083b94cade77747368a5b40c03
+size 4988184
--- a/imatrix.dataset
+++ b/imatrix.dataset
--- a/imatrix.log
+++ b/imatrix.log
@@ -0,0 +1,151 @@
+main: build = 3006 (eaf6e031)
+main: built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
+main: seed  = 1716806623
+llama_model_loader: loaded meta data with 22 key-value pairs and 291 tensors from openchat-3.6-8b-20240522-IMat-GGUF/openchat-3.6-8b-20240522.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              = llama
+llama_model_loader: - kv   1:                               general.name str              = openchat-3.6-8b-20240522
+llama_model_loader: - kv   2:                          llama.block_count u32              = 32
+llama_model_loader: - kv   3:                       llama.context_length u32              = 8192
+llama_model_loader: - kv   4:                     llama.embedding_length u32              = 4096
+llama_model_loader: - kv   5:                  llama.feed_forward_length u32              = 14336
+llama_model_loader: - kv   6:                 llama.attention.head_count u32              = 32
+llama_model_loader: - kv   7:              llama.attention.head_count_kv u32              = 8
+llama_model_loader: - kv   8:                       llama.rope.freq_base f32              = 500000.000000
+llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
+llama_model_loader: - kv  10:                          general.file_type u32              = 1
+llama_model_loader: - kv  11:                           llama.vocab_size u32              = 128256
+llama_model_loader: - kv  12:                 llama.rope.dimension_count u32              = 128
+llama_model_loader: - kv  13:                       tokenizer.ggml.model str              = gpt2
+llama_model_loader: - kv  14:                         tokenizer.ggml.pre str              = llama-bpe
+llama_model_loader: - kv  15:                      tokenizer.ggml.tokens arr[str,128256]  = ["!", "\"", "#", "$", "%", "&", "'", ...
+llama_model_loader: - kv  16:                  tokenizer.ggml.token_type arr[i32,128256]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
+llama_model_loader: - kv  17:                      tokenizer.ggml.merges arr[str,280147]  = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
+llama_model_loader: - kv  18:                tokenizer.ggml.bos_token_id u32              = 128000
+llama_model_loader: - kv  19:                tokenizer.ggml.eos_token_id u32              = 128009
+llama_model_loader: - kv  20:                    tokenizer.chat_template str              = {{ bos_token }}{% for message in mess...
+llama_model_loader: - kv  21:               general.quantization_version u32              = 2
+llama_model_loader: - type  f32:   65 tensors
+llama_model_loader: - type  f16:  226 tensors
+llm_load_vocab: special tokens definition check successful ( 256/128256 ).
+llm_load_print_meta: format           = GGUF V3 (latest)
+llm_load_print_meta: arch             = llama
+llm_load_print_meta: vocab type       = BPE
+llm_load_print_meta: n_vocab          = 128256
+llm_load_print_meta: n_merges         = 280147
+llm_load_print_meta: n_ctx_train      = 8192
+llm_load_print_meta: n_embd           = 4096
+llm_load_print_meta: n_head           = 32
+llm_load_print_meta: n_head_kv        = 8
+llm_load_print_meta: n_layer          = 32
+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            = 4
+llm_load_print_meta: n_embd_k_gqa     = 1024
+llm_load_print_meta: n_embd_v_gqa     = 1024
+llm_load_print_meta: f_norm_eps       = 0.0e+00
+llm_load_print_meta: f_norm_rms_eps   = 1.0e-05
+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             = 14336
+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        = 0
+llm_load_print_meta: rope scaling     = linear
+llm_load_print_meta: freq_base_train  = 500000.0
+llm_load_print_meta: freq_scale_train = 1
+llm_load_print_meta: n_yarn_orig_ctx  = 8192
+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       = 8B
+llm_load_print_meta: model ftype      = F16
+llm_load_print_meta: model params     = 8.03 B
+llm_load_print_meta: model size       = 14.96 GiB (16.00 BPW) 
+llm_load_print_meta: general.name     = openchat-3.6-8b-20240522
+llm_load_print_meta: BOS token        = 128000 '<|begin_of_text|>'
+llm_load_print_meta: EOS token        = 128009 '<|eot_id|>'
+llm_load_print_meta: LF token         = 128 'Ä'
+llm_load_print_meta: EOT token        = 128009 '<|eot_id|>'
+ggml_cuda_init: GGML_CUDA_FORCE_MMQ:   no
+ggml_cuda_init: CUDA_USE_TENSOR_CORES: yes
+ggml_cuda_init: found 1 CUDA devices:
+  Device 0: NVIDIA GeForce RTX 4090, compute capability 8.9, VMM: yes
+llm_load_tensors: ggml ctx size =    0.30 MiB
+llm_load_tensors: offloading 32 repeating layers to GPU
+llm_load_tensors: offloading non-repeating layers to GPU
+llm_load_tensors: offloaded 33/33 layers to GPU
+llm_load_tensors:        CPU buffer size =  1002.00 MiB
+llm_load_tensors:      CUDA0 buffer size = 14315.02 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  = 500000.0
+llama_new_context_with_model: freq_scale = 1
+llama_kv_cache_init:      CUDA0 KV buffer size =    64.00 MiB
+llama_new_context_with_model: KV self size  =   64.00 MiB, K (f16):   32.00 MiB, V (f16):   32.00 MiB
+llama_new_context_with_model:  CUDA_Host  output buffer size =     0.49 MiB
+llama_new_context_with_model:      CUDA0 compute buffer size =   258.50 MiB
+llama_new_context_with_model:  CUDA_Host compute buffer size =     9.01 MiB
+llama_new_context_with_model: graph nodes  = 1030
+llama_new_context_with_model: graph splits = 2
+
+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 70.503 ms
+compute_imatrix: computing over 189 chunks with batch_size 512
+compute_imatrix: 0.43 seconds per pass - ETA 1.35 minutes
+[1]6.0348,[2]4.7804,[3]4.3377,[4]5.4029,[5]5.5439,[6]4.7045,[7]5.0585,[8]5.5263,[9]5.7295,
+save_imatrix: stored collected data after 10 chunks in openchat-3.6-8b-20240522-IMat-GGUF/imatrix.dat
+[10]5.7404,[11]6.2072,[12]5.9627,[13]6.4471,[14]6.8690,[15]7.1301,[16]7.5406,[17]7.9763,[18]8.1476,[19]7.7801,
+save_imatrix: stored collected data after 20 chunks in openchat-3.6-8b-20240522-IMat-GGUF/imatrix.dat
+[20]7.6815,[21]7.4206,[22]6.9722,[23]6.6753,[24]6.5744,[25]6.7881,[26]6.9148,[27]7.0631,[28]7.0700,[29]6.7843,
+save_imatrix: stored collected data after 30 chunks in openchat-3.6-8b-20240522-IMat-GGUF/imatrix.dat
+[30]6.6068,[31]6.5076,[32]6.4810,[33]6.4494,[34]6.4542,[35]6.5629,[36]6.6907,[37]6.8445,[38]6.8942,[39]7.0491,
+save_imatrix: stored collected data after 40 chunks in openchat-3.6-8b-20240522-IMat-GGUF/imatrix.dat
+[40]7.2272,[41]7.4645,[42]7.5906,[43]7.7612,[44]7.7605,[45]7.7814,[46]7.8920,[47]8.0201,[48]8.0505,[49]8.1362,
+save_imatrix: stored collected data after 50 chunks in openchat-3.6-8b-20240522-IMat-GGUF/imatrix.dat
+[50]8.1781,[51]8.2467,[52]8.2276,[53]8.2640,[54]8.2626,[55]8.2506,[56]8.2139,[57]8.2284,[58]8.3023,[59]8.4184,
+save_imatrix: stored collected data after 60 chunks in openchat-3.6-8b-20240522-IMat-GGUF/imatrix.dat
+[60]8.5066,[61]8.4251,[62]8.3594,[63]8.2943,[64]8.2607,[65]8.1936,[66]8.1153,[67]8.0173,[68]8.0054,[69]7.9513,
+save_imatrix: stored collected data after 70 chunks in openchat-3.6-8b-20240522-IMat-GGUF/imatrix.dat
+[70]7.9827,[71]8.0265,[72]8.0360,[73]8.0271,[74]8.0691,[75]7.9830,[76]7.9466,[77]7.8510,[78]7.8160,[79]7.7771,
+save_imatrix: stored collected data after 80 chunks in openchat-3.6-8b-20240522-IMat-GGUF/imatrix.dat
+[80]7.7414,[81]7.6666,[82]7.5859,[83]7.5116,[84]7.5245,[85]7.5625,[86]7.5638,[87]7.5269,[88]7.5130,[89]7.5259,
+save_imatrix: stored collected data after 90 chunks in openchat-3.6-8b-20240522-IMat-GGUF/imatrix.dat
+[90]7.5618,[91]7.5482,[92]7.5582,[93]7.5827,[94]7.6174,[95]7.5908,[96]7.6124,[97]7.6184,[98]7.6096,[99]7.6157,
+save_imatrix: stored collected data after 100 chunks in openchat-3.6-8b-20240522-IMat-GGUF/imatrix.dat
+[100]7.6085,[101]7.5939,[102]7.5922,[103]7.6202,[104]7.6382,[105]7.6315,[106]7.6544,[107]7.6763,[108]7.6100,[109]7.6095,
+save_imatrix: stored collected data after 110 chunks in openchat-3.6-8b-20240522-IMat-GGUF/imatrix.dat
+[110]7.5896,[111]7.5451,[112]7.5181,[113]7.4785,[114]7.4304,[115]7.3814,[116]7.3309,[117]7.2866,[118]7.2428,[119]7.2931,
+save_imatrix: stored collected data after 120 chunks in openchat-3.6-8b-20240522-IMat-GGUF/imatrix.dat
+[120]7.3070,[121]7.3335,[122]7.3880,[123]7.4235,[124]7.4814,[125]7.5484,[126]7.6088,[127]7.6668,[128]7.7422,[129]7.8223,
+save_imatrix: stored collected data after 130 chunks in openchat-3.6-8b-20240522-IMat-GGUF/imatrix.dat
+[130]7.7887,[131]7.8083,[132]7.8176,[133]7.8402,[134]7.8135,[135]7.8121,[136]7.8459,[137]7.8508,[138]7.8611,[139]7.8849,
+save_imatrix: stored collected data after 140 chunks in openchat-3.6-8b-20240522-IMat-GGUF/imatrix.dat
+[140]7.8981,[141]7.8929,[142]7.9079,[143]7.8729,[144]7.8877,[145]7.9220,[146]7.9362,[147]7.9369,[148]7.9497,[149]7.9625,
+save_imatrix: stored collected data after 150 chunks in openchat-3.6-8b-20240522-IMat-GGUF/imatrix.dat
+[150]7.9463,[151]7.9322,[152]7.9401,[153]7.9533,[154]8.0047,[155]7.9772,[156]7.9799,[157]8.0199,[158]8.0687,[159]8.1549,
+save_imatrix: stored collected data after 160 chunks in openchat-3.6-8b-20240522-IMat-GGUF/imatrix.dat
+[160]8.2253,[161]8.2376,[162]8.2574,[163]8.2741,[164]8.2780,[165]8.3119,[166]8.3076,[167]8.3057,[168]8.3136,[169]8.3367,
+save_imatrix: stored collected data after 170 chunks in openchat-3.6-8b-20240522-IMat-GGUF/imatrix.dat
+[170]8.3299,[171]8.3237,[172]8.3376,[173]8.3447,[174]8.3637,[175]8.3477,[176]8.3407,[177]8.3396,[178]8.3359,[179]8.3239,
+save_imatrix: stored collected data after 180 chunks in openchat-3.6-8b-20240522-IMat-GGUF/imatrix.dat
+[180]8.3046,[181]8.3154,[182]8.2919,[183]8.3189,[184]8.3258,[185]8.3672,[186]8.3911,[187]8.4162,[188]8.3767,[189]8.3368,
+save_imatrix: stored collected data after 189 chunks in openchat-3.6-8b-20240522-IMat-GGUF/imatrix.dat
+
+llama_print_timings:        load time =    2087.30 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 =   65137.26 ms / 96768 tokens (    0.67 ms per token,  1485.60 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 =   67989.82 ms / 96769 tokens
+
+Final estimate: PPL = 8.3368 +/- 0.10059
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