Upload GPTQ quantized model (group_size=32)

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,112 @@
+---
+license: apache-2.0
+base_model: Kwaipilot/KAT-Dev-72B-Exp
+tags:
+- gptq
+- quantized
+- vllm
+- 4bit
+- group_size_32
+quantization_config:
+  quant_method: gptq
+  bits: 4
+  group_size: 32
+  damp_percent: 0.1
+---
+
+# KAT-Dev-72B-Exp - GPTQ INT4 (group_size=32)
+
+This is a GPTQ quantized version of [Kwaipilot/KAT-Dev-72B-Exp](https://huggingface.co/Kwaipilot/KAT-Dev-72B-Exp).
+
+## Quantization Details
+
+- **Method**: GPTQ (GPT Quantization)
+- **Bits**: 4
+- **Group Size**: 32
+- **Quantization Type**: INT
+- **Symmetric**: True
+- **Calibration Samples**: 128
+- **Calibration Dataset**: allenai/c4
+- **Max Sequence Length**: 512
+
+## Hardware Used for Quantization
+
+- 6x NVIDIA GeForce RTX 5090 (32GB each)
+- CUDA 12.8+
+- Sequential layer-by-layer processing (OOM-safe)
+
+## Usage
+
+### With vLLM
+
+```python
+from vllm import LLM, SamplingParams
+
+# Initialize the model
+llm = LLM(model="Vykyan/KAT-Dev-72B-Exp-GPTQ-INT4-gs32", trust_remote_code=True)
+
+# Create sampling parameters
+sampling_params = SamplingParams(
+    temperature=0.7,
+    top_p=0.9,
+    max_tokens=512,
+)
+
+# Generate text
+prompts = ["Hello, how are you?"]
+outputs = llm.generate(prompts, sampling_params)
+
+for output in outputs:
+    print(output.outputs[0].text)
+```
+
+### With Transformers
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained(
+    "Vykyan/KAT-Dev-72B-Exp-GPTQ-INT4-gs32",
+    device_map="auto",
+    trust_remote_code=True
+)
+tokenizer = AutoTokenizer.from_pretrained(
+    "Vykyan/KAT-Dev-72B-Exp-GPTQ-INT4-gs32",
+    trust_remote_code=True
+)
+
+# Generate
+inputs = tokenizer("Hello, how are you?", return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=100)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Inference Performance
+
+This quantized model offers:
+- ~4x memory reduction compared to FP16
+- Faster inference on compatible hardware
+- Maintained accuracy through GPTQ quantization
+
+### Recommended Hardware
+
+- NVIDIA GPUs with compute capability 7.5+ (RTX 20-series or newer)
+- Minimum 24GB VRAM for single-GPU inference
+- Multi-GPU setup for larger batch sizes
+
+## Model Details
+
+- **Base Model**: Kwaipilot/KAT-Dev-72B-Exp
+- **Quantization Tool**: llm-compressor
+- **Compatible Inference Engines**: vLLM, TGI (Text Generation Inference)
+
+## Limitations
+
+- Quantization may affect model accuracy on certain tasks
+- Requires vLLM or compatible inference engine for optimal performance
+
+## Acknowledgements
+
+- Base model: [Kwaipilot/KAT-Dev-72B-Exp](https://huggingface.co/Kwaipilot/KAT-Dev-72B-Exp)
+- Quantization: [llm-compressor](https://github.com/vllm-project/llm-compressor)
+- Inference: [vLLM](https://github.com/vllm-project/vllm)

added_tokens.json

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+{
+  "</tool_call>": 151658,
+  "<tool_call>": 151657,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
+  "<|fim_prefix|>": 151659,
+  "<|fim_suffix|>": 151661,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644,
+  "<|image_pad|>": 151655,
+  "<|object_ref_end|>": 151647,
+  "<|object_ref_start|>": 151646,
+  "<|quad_end|>": 151651,
+  "<|quad_start|>": 151650,
+  "<|repo_name|>": 151663,
+  "<|video_pad|>": 151656,
+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
+  "<|vision_start|>": 151652
+}

chat_template.jinja

@@ -0,0 +1,54 @@
+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
+    {%- endif %}
+    {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
+    {%- else %}
+        {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

config.json

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+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "eos_token_id": 151645,
+  "hidden_act": "silu",
+  "hidden_size": 8192,
+  "initializer_range": 0.02,
+  "intermediate_size": 29568,
+  "max_position_embeddings": 131072,
+  "max_window_layers": 70,
+  "model_type": "qwen2",
+  "num_attention_heads": 64,
+  "num_hidden_layers": 80,
+  "num_key_value_heads": 8,
+  "pad_token_id": 151643,
+  "quantization_config": {
+    "config_groups": {
+      "group_0": {
+        "input_activations": null,
+        "output_activations": null,
+        "targets": [
+          "Linear"
+        ],
+        "weights": {
+          "actorder": null,
+          "block_structure": null,
+          "dynamic": false,
+          "group_size": 32,
+          "num_bits": 4,
+          "observer": "minmax",
+          "observer_kwargs": {},
+          "strategy": "group",
+          "symmetric": true,
+          "type": "int"
+        }
+      }
+    },
+    "format": "pack-quantized",
+    "global_compression_ratio": null,
+    "ignore": [
+      "lm_head"
+    ],
+    "kv_cache_scheme": null,
+    "quant_method": "compressed-tensors",
+    "quantization_status": "compressed"
+  },
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "sliding_window": 131072,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.52.4",
+  "use_cache": false,
+  "use_sliding_window": false,
+  "vocab_size": 152064
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 151643,
+  "eos_token_id": 151645,
+  "transformers_version": "4.52.4",
+  "use_cache": false
+}

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recipe.yaml

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+default_stage:
+  default_modifiers:
+    GPTQModifier:
+      config_groups:
+        group_0:
+          targets: [Linear]
+          weights: {num_bits: 4, type: int, symmetric: true, group_size: 32, strategy: group,
+            observer: minmax}
+          input_activations: null
+          output_activations: null
+      ignore: [lm_head]
+      dampening_frac: 0.1

special_tokens_map.json

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+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

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+size 11421896

tokenizer_config.json

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+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "normalized": false,
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+    "151664": {
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+  "additional_special_tokens": [
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+    "<|im_end|>",
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+    "<|object_ref_end|>",
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+    "<|vision_end|>",
+    "<|vision_pad|>",
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+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}