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Model: legraphista/internlm2_5-7b-chat-1m-IMat-GGUF Source: Original Platform
2026-09-10 05:17:17 +08:00
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+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+*tfevents* filter=lfs diff=lfs merge=lfs -text
+imatrix.dat filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.Q5_K.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.BF16.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.Q4_K.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.Q3_K.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.FP16.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.Q2_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.IQ4_NL.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.IQ4_XS.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.IQ3_M.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.IQ3_S.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.IQ3_XS.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.IQ3_XXS.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.IQ2_M.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.IQ2_S.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.IQ2_XS.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.IQ2_XXS.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.IQ1_M.gguf filter=lfs diff=lfs merge=lfs -text
+internlm2_5-7b-chat-1m.IQ1_S.gguf filter=lfs diff=lfs merge=lfs -text
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+---
+base_model: internlm/internlm2_5-7b-chat-1m
+inference: false
+library_name: gguf
+license: other
+pipeline_tag: text-generation
+quantized_by: legraphista
+tags:
+- quantized
+- GGUF
+- quantization
+- imat
+- imatrix
+- static
+- 16bit
+- 8bit
+- 6bit
+- 5bit
+- 4bit
+- 3bit
+- 2bit
+- 1bit
+---
+
+# internlm2_5-7b-chat-1m-IMat-GGUF
+_Llama.cpp imatrix quantization of internlm/internlm2_5-7b-chat-1m_
+
+Original Model: [internlm/internlm2_5-7b-chat-1m](https://huggingface.co/internlm/internlm2_5-7b-chat-1m)    
+Original dtype: `BF16` (`bfloat16`)  
+Quantized by:  llama.cpp [b3289](https://github.com/ggerganov/llama.cpp/releases/tag/b3289)  
+IMatrix dataset: [here](https://gist.githubusercontent.com/bartowski1182/eb213dccb3571f863da82e99418f81e8/raw/b2869d80f5c16fd7082594248e80144677736635/calibration_datav3.txt)  
+
+- [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/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/imatrix.dat)
+
+### Common Quants
+| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
+| -------- | ---------- | --------- | ------ | ------------ | -------- |
+| [internlm2_5-7b-chat-1m.Q8_0.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.Q8_0.gguf) | Q8_0 | 8.22GB | ✅ Available | ⚪ Static | 📦 No
+| [internlm2_5-7b-chat-1m.Q6_K.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.Q6_K.gguf) | Q6_K | 6.35GB | ✅ Available | ⚪ Static | 📦 No
+| [internlm2_5-7b-chat-1m.Q4_K.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.Q4_K.gguf) | Q4_K | 4.71GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.Q3_K.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.Q3_K.gguf) | Q3_K | 3.83GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.Q2_K.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.Q2_K.gguf) | Q2_K | 3.01GB | ✅ Available | 🟢 IMatrix | 📦 No
+
+
+### All Quants
+| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
+| -------- | ---------- | --------- | ------ | ------------ | -------- |
+| [internlm2_5-7b-chat-1m.BF16.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.BF16.gguf) | BF16 | 15.48GB | ✅ Available | ⚪ Static | 📦 No
+| [internlm2_5-7b-chat-1m.FP16.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.FP16.gguf) | F16 | 15.48GB | ✅ Available | ⚪ Static | 📦 No
+| [internlm2_5-7b-chat-1m.Q8_0.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.Q8_0.gguf) | Q8_0 | 8.22GB | ✅ Available | ⚪ Static | 📦 No
+| [internlm2_5-7b-chat-1m.Q6_K.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.Q6_K.gguf) | Q6_K | 6.35GB | ✅ Available | ⚪ Static | 📦 No
+| [internlm2_5-7b-chat-1m.Q5_K.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.Q5_K.gguf) | Q5_K | 5.51GB | ✅ Available | ⚪ Static | 📦 No
+| [internlm2_5-7b-chat-1m.Q5_K_S.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.Q5_K_S.gguf) | Q5_K_S | 5.37GB | ✅ Available | ⚪ Static | 📦 No
+| [internlm2_5-7b-chat-1m.Q4_K.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.Q4_K.gguf) | Q4_K | 4.71GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.Q4_K_S.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.Q4_K_S.gguf) | Q4_K_S | 4.48GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.IQ4_NL.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.IQ4_NL.gguf) | IQ4_NL | 4.47GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.IQ4_XS.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.IQ4_XS.gguf) | IQ4_XS | 4.24GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.Q3_K.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.Q3_K.gguf) | Q3_K | 3.83GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.Q3_K_L.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.Q3_K_L.gguf) | Q3_K_L | 4.13GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.Q3_K_S.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.Q3_K_S.gguf) | Q3_K_S | 3.48GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.IQ3_M.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.IQ3_M.gguf) | IQ3_M | 3.60GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.IQ3_S.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.IQ3_S.gguf) | IQ3_S | 3.49GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.IQ3_XS.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.IQ3_XS.gguf) | IQ3_XS | 3.33GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.IQ3_XXS.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.IQ3_XXS.gguf) | IQ3_XXS | 3.11GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.Q2_K.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.Q2_K.gguf) | Q2_K | 3.01GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.Q2_K_S.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.Q2_K_S.gguf) | Q2_K_S | 2.82GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.IQ2_M.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.IQ2_M.gguf) | IQ2_M | 2.78GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.IQ2_S.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.IQ2_S.gguf) | IQ2_S | 2.59GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.IQ2_XS.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.IQ2_XS.gguf) | IQ2_XS | 2.45GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.IQ2_XXS.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.IQ2_XXS.gguf) | IQ2_XXS | 2.24GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.IQ1_M.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.IQ1_M.gguf) | IQ1_M | 2.01GB | ✅ Available | 🟢 IMatrix | 📦 No
+| [internlm2_5-7b-chat-1m.IQ1_S.gguf](https://huggingface.co/legraphista/internlm2_5-7b-chat-1m-IMat-GGUF/blob/main/internlm2_5-7b-chat-1m.IQ1_S.gguf) | IQ1_S | 1.87GB | ✅ 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/internlm2_5-7b-chat-1m-IMat-GGUF --include "internlm2_5-7b-chat-1m.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/internlm2_5-7b-chat-1m-IMat-GGUF --include "internlm2_5-7b-chat-1m.Q8_0/*" --local-dir ./
+# see FAQ for merging GGUF's
+```
+
+---
+
+## Inference
+
+### Simple chat template
+```
+<s><|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
+```
+<s><|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 internlm2_5-7b-chat-1m.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: `internlm2_5-7b-chat-1m.Q8_0`)
+3. Run `gguf-split --merge internlm2_5-7b-chat-1m.Q8_0/internlm2_5-7b-chat-1m.Q8_0-00001-of-XXXXX.gguf internlm2_5-7b-chat-1m.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:da5d8b217a749124bf3f18a7931b26dbbc97048795e2755e70460cf5f03de0aa
+size 4988182
--- a/imatrix.dataset
+++ b/imatrix.dataset
--- a/imatrix.log
+++ b/imatrix.log
@@ -0,0 +1,144 @@
+llama_model_loader: loaded meta data with 24 key-value pairs and 291 tensors from internlm2_5-7b-chat-1m-IMat-GGUF/internlm2_5-7b-chat-1m.Q8_0.gguf.hardlink.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              = internlm2
+llama_model_loader: - kv   1:                               general.name str              = InternLM2
+llama_model_loader: - kv   2:                   internlm2.context_length u32              = 262144
+llama_model_loader: - kv   3:                      internlm2.block_count u32              = 32
+llama_model_loader: - kv   4:                 internlm2.embedding_length u32              = 4096
+llama_model_loader: - kv   5:              internlm2.feed_forward_length u32              = 14336
+llama_model_loader: - kv   6:                   internlm2.rope.freq_base f32              = 50000000.000000
+llama_model_loader: - kv   7:             internlm2.attention.head_count u32              = 32
+llama_model_loader: - kv   8: internlm2.attention.layer_norm_rms_epsilon f32              = 0.000010
+llama_model_loader: - kv   9:          internlm2.attention.head_count_kv u32              = 8
+llama_model_loader: - kv  10:                          general.file_type u32              = 7
+llama_model_loader: - kv  11:                       tokenizer.ggml.model str              = llama
+llama_model_loader: - kv  12:                         tokenizer.ggml.pre str              = default
+llama_model_loader: - kv  13:                      tokenizer.ggml.tokens arr[str,92544]   = ["<unk>", "<s>", "</s>", "<0x00>", "<...
+llama_model_loader: - kv  14:                      tokenizer.ggml.scores arr[f32,92544]   = [0.000000, 0.000000, 0.000000, 0.0000...
+llama_model_loader: - kv  15:                  tokenizer.ggml.token_type arr[i32,92544]   = [2, 3, 3, 6, 6, 6, 6, 6, 6, 6, 6, 6, ...
+llama_model_loader: - kv  16:            tokenizer.ggml.add_space_prefix bool             = false
+llama_model_loader: - kv  17:                tokenizer.ggml.bos_token_id u32              = 1
+llama_model_loader: - kv  18:                tokenizer.ggml.eos_token_id u32              = 92542
+llama_model_loader: - kv  19:            tokenizer.ggml.padding_token_id u32              = 2
+llama_model_loader: - kv  20:               tokenizer.ggml.add_bos_token bool             = true
+llama_model_loader: - kv  21:               tokenizer.ggml.add_eos_token bool             = false
+llama_model_loader: - kv  22:                    tokenizer.chat_template str              = {{ bos_token }}{% for message in mess...
+llama_model_loader: - kv  23:               general.quantization_version u32              = 2
+llama_model_loader: - type  f32:   65 tensors
+llama_model_loader: - type q8_0:  226 tensors
+llm_load_vocab: special tokens cache size = 259
+llm_load_vocab: token to piece cache size = 0.5531 MB
+llm_load_print_meta: format           = GGUF V3 (latest)
+llm_load_print_meta: arch             = internlm2
+llm_load_print_meta: vocab type       = SPM
+llm_load_print_meta: n_vocab          = 92544
+llm_load_print_meta: n_merges         = 0
+llm_load_print_meta: n_ctx_train      = 262144
+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_swa            = 0
+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  = 50000000.0
+llm_load_print_meta: freq_scale_train = 1
+llm_load_print_meta: n_ctx_orig_yarn  = 262144
+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       = 7B
+llm_load_print_meta: model ftype      = Q8_0
+llm_load_print_meta: model params     = 7.74 B
+llm_load_print_meta: model size       = 7.66 GiB (8.50 BPW) 
+llm_load_print_meta: general.name     = InternLM2
+llm_load_print_meta: BOS token        = 1 '<s>'
+llm_load_print_meta: EOS token        = 92542 '[UNUSED_TOKEN_145]'
+llm_load_print_meta: UNK token        = 0 '<unk>'
+llm_load_print_meta: PAD token        = 2 '</s>'
+llm_load_print_meta: LF token         = 13 '<0x0A>'
+llm_load_print_meta: max token length = 384
+ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
+ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
+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 =    0.27 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 =   384.09 MiB
+llm_load_tensors:      CUDA0 buffer size =  7457.11 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  = 50000000.0
+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 =     0.35 MiB
+llama_new_context_with_model:      CUDA0 compute buffer size =   188.75 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 103.571 ms
+compute_imatrix: computing over 136 chunks with batch_size 512
+compute_imatrix: 0.57 seconds per pass - ETA 1.28 minutes
+[1]5.0346,[2]3.6723,[3]3.5707,[4]4.0879,[5]4.0274,[6]3.6532,[7]4.3100,[8]4.3760,[9]4.8143,
+save_imatrix: stored collected data after 10 chunks in internlm2_5-7b-chat-1m-IMat-GGUF/imatrix.dat
+[10]4.9549,[11]4.5921,[12]4.9100,[13]5.5257,[14]5.8588,[15]6.3237,[16]6.5349,[17]6.2162,[18]6.4203,[19]6.7455,
+save_imatrix: stored collected data after 20 chunks in internlm2_5-7b-chat-1m-IMat-GGUF/imatrix.dat
+[20]6.4964,[21]6.5862,[22]6.6543,[23]6.6712,[24]6.5913,[25]6.7950,[26]7.0111,[27]7.1811,[28]7.2316,[29]7.3379,
+save_imatrix: stored collected data after 30 chunks in internlm2_5-7b-chat-1m-IMat-GGUF/imatrix.dat
+[30]7.5555,[31]7.6303,[32]7.3712,[33]7.0776,[34]6.7896,[35]6.5375,[36]6.3935,[37]6.2858,[38]6.2133,[39]6.1529,
+save_imatrix: stored collected data after 40 chunks in internlm2_5-7b-chat-1m-IMat-GGUF/imatrix.dat
+[40]6.0788,[41]6.0151,[42]5.9126,[43]5.8695,[44]5.9202,[45]5.9750,[46]6.1160,[47]6.1016,[48]6.3090,[49]6.4878,
+save_imatrix: stored collected data after 50 chunks in internlm2_5-7b-chat-1m-IMat-GGUF/imatrix.dat
+[50]6.6539,[51]6.7808,[52]6.9489,[53]6.8259,[54]6.9078,[55]6.9920,[56]7.1027,[57]6.9751,[58]6.9850,[59]7.0143,
+save_imatrix: stored collected data after 60 chunks in internlm2_5-7b-chat-1m-IMat-GGUF/imatrix.dat
+[60]7.1009,[61]7.2276,[62]7.3030,[63]7.3550,[64]7.3615,[65]7.3773,[66]7.3610,[67]7.3245,[68]7.2521,[69]7.2307,
+save_imatrix: stored collected data after 70 chunks in internlm2_5-7b-chat-1m-IMat-GGUF/imatrix.dat
+[70]7.2776,[71]7.2967,[72]7.2223,[73]7.1809,[74]7.1856,[75]7.1442,[76]7.1218,[77]7.1049,[78]7.1137,[79]7.0665,
+save_imatrix: stored collected data after 80 chunks in internlm2_5-7b-chat-1m-IMat-GGUF/imatrix.dat
+[80]7.0704,[81]7.0205,[82]6.9936,[83]6.9500,[84]6.9328,[85]6.8774,[86]6.8457,[87]6.8165,[88]6.8428,[89]6.8503,
+save_imatrix: stored collected data after 90 chunks in internlm2_5-7b-chat-1m-IMat-GGUF/imatrix.dat
+[90]6.8185,[91]6.8376,[92]6.8526,[93]6.8059,[94]6.7976,[95]6.7873,[96]6.8087,[97]6.8044,[98]6.8017,[99]6.7634,
+save_imatrix: stored collected data after 100 chunks in internlm2_5-7b-chat-1m-IMat-GGUF/imatrix.dat
+[100]6.7333,[101]6.6953,[102]6.6538,[103]6.6212,[104]6.5844,[105]6.5521,[106]6.5216,[107]6.5282,[108]6.5647,[109]6.6344,
+save_imatrix: stored collected data after 110 chunks in internlm2_5-7b-chat-1m-IMat-GGUF/imatrix.dat
+[110]6.6972,[111]6.7546,[112]6.8547,[113]6.9219,[114]6.9492,[115]6.9457,[116]6.9581,[117]6.9503,[118]6.9399,[119]6.8934,
+save_imatrix: stored collected data after 120 chunks in internlm2_5-7b-chat-1m-IMat-GGUF/imatrix.dat
+[120]6.8699,[121]6.9023,[122]6.9007,[123]6.9027,[124]6.9205,[125]6.9609,[126]6.9884,[127]6.9980,[128]7.0215,[129]7.0489,
+save_imatrix: stored collected data after 130 chunks in internlm2_5-7b-chat-1m-IMat-GGUF/imatrix.dat
+[130]7.0098,[131]7.0461,[132]7.1022,[133]7.1359,[134]7.1953,[135]7.2389,[136]7.2832,
+save_imatrix: stored collected data after 136 chunks in internlm2_5-7b-chat-1m-IMat-GGUF/imatrix.dat
+
+llama_print_timings:        load time =    1840.88 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 =   71070.73 ms / 69632 tokens (    1.02 ms per token,   979.76 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 =   73099.32 ms / 69633 tokens
+
+Final estimate: PPL = 7.2832 +/- 0.09853
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