Text Generation
Transformers
Safetensors
English
qwen2
quantized
gptq
4bit
safety-evaluation
banterhearts
conversational
text-generation-inference
4-bit precision
Instructions to use Crusadersk/qwen2.5-1.5b-gptq-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Crusadersk/qwen2.5-1.5b-gptq-4bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Crusadersk/qwen2.5-1.5b-gptq-4bit") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Crusadersk/qwen2.5-1.5b-gptq-4bit") model = AutoModelForCausalLM.from_pretrained("Crusadersk/qwen2.5-1.5b-gptq-4bit", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Crusadersk/qwen2.5-1.5b-gptq-4bit with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Crusadersk/qwen2.5-1.5b-gptq-4bit" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Crusadersk/qwen2.5-1.5b-gptq-4bit", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Crusadersk/qwen2.5-1.5b-gptq-4bit
- SGLang
How to use Crusadersk/qwen2.5-1.5b-gptq-4bit with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Crusadersk/qwen2.5-1.5b-gptq-4bit" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Crusadersk/qwen2.5-1.5b-gptq-4bit", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Crusadersk/qwen2.5-1.5b-gptq-4bit" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Crusadersk/qwen2.5-1.5b-gptq-4bit", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Crusadersk/qwen2.5-1.5b-gptq-4bit with Docker Model Runner:
docker model run hf.co/Crusadersk/qwen2.5-1.5b-gptq-4bit
Self-quantized qwen2.5-1.5b-gptq 4-bit (group_size=128, seed=42)
Browse files- .gitattributes +1 -0
- chat_template.jinja +54 -0
- config.json +103 -0
- generation_config.json +13 -0
- model.safetensors +3 -0
- quant_log.csv +197 -0
- quantize_config.json +7 -0
- quantize_manifest.json +12 -0
- tokenizer.json +3 -0
- tokenizer_config.json +30 -0
.gitattributes
CHANGED
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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chat_template.jinja
ADDED
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@@ -0,0 +1,54 @@
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| 1 |
+
{%- if tools %}
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| 2 |
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{{- '<|im_start|>system\n' }}
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| 3 |
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{%- if messages[0]['role'] == 'system' %}
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| 4 |
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{{- messages[0]['content'] }}
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| 5 |
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{%- else %}
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| 6 |
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{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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| 7 |
+
{%- endif %}
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| 8 |
+
{{- "\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>" }}
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| 9 |
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{%- for tool in tools %}
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{{- "\n" }}
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| 11 |
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{{- tool | tojson }}
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{%- endfor %}
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| 13 |
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{{- "\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" }}
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| 14 |
+
{%- else %}
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| 15 |
+
{%- if messages[0]['role'] == 'system' %}
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| 16 |
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{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
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| 17 |
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{%- else %}
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| 18 |
+
{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
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| 19 |
+
{%- endif %}
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| 20 |
+
{%- endif %}
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| 21 |
+
{%- for message in messages %}
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| 22 |
+
{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
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| 23 |
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{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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| 24 |
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{%- elif message.role == "assistant" %}
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| 25 |
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{{- '<|im_start|>' + message.role }}
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| 26 |
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{%- if message.content %}
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| 27 |
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{{- '\n' + message.content }}
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| 28 |
+
{%- endif %}
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| 29 |
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{%- for tool_call in message.tool_calls %}
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| 30 |
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{%- if tool_call.function is defined %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '\n<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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| 36 |
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{{- tool_call.arguments | tojson }}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{{- '<|im_end|>\n' }}
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| 40 |
+
{%- elif message.role == "tool" %}
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| 41 |
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{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
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| 42 |
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{{- '<|im_start|>user' }}
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{%- endif %}
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| 44 |
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{{- '\n<tool_response>\n' }}
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| 45 |
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{{- message.content }}
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{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|im_start|>assistant\n' }}
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{%- endif %}
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config.json
ADDED
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@@ -0,0 +1,103 @@
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{
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| 2 |
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"architectures": [
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| 3 |
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"Qwen2ForCausalLM"
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],
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| 5 |
+
"attention_dropout": 0.0,
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| 6 |
+
"bos_token_id": 151643,
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| 7 |
+
"dtype": "bfloat16",
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| 8 |
+
"eos_token_id": 151645,
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| 9 |
+
"hidden_act": "silu",
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| 10 |
+
"hidden_size": 1536,
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| 11 |
+
"initializer_range": 0.02,
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| 12 |
+
"intermediate_size": 8960,
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| 13 |
+
"layer_types": [
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| 14 |
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"full_attention",
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| 15 |
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"full_attention",
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| 16 |
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"full_attention",
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| 17 |
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"full_attention",
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| 18 |
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"full_attention",
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| 19 |
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"full_attention",
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| 20 |
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"full_attention",
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| 21 |
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"full_attention",
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| 22 |
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"full_attention",
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| 23 |
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"full_attention",
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| 24 |
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"full_attention",
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| 25 |
+
"full_attention",
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| 26 |
+
"full_attention",
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| 27 |
+
"full_attention",
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| 28 |
+
"full_attention",
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| 29 |
+
"full_attention",
|
| 30 |
+
"full_attention",
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| 31 |
+
"full_attention",
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| 32 |
+
"full_attention",
|
| 33 |
+
"full_attention",
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| 34 |
+
"full_attention",
|
| 35 |
+
"full_attention",
|
| 36 |
+
"full_attention",
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| 37 |
+
"full_attention",
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| 38 |
+
"full_attention",
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| 39 |
+
"full_attention",
|
| 40 |
+
"full_attention",
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| 41 |
+
"full_attention"
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| 42 |
+
],
|
| 43 |
+
"max_position_embeddings": 32768,
|
| 44 |
+
"max_window_layers": 21,
|
| 45 |
+
"model_type": "qwen2",
|
| 46 |
+
"num_attention_heads": 12,
|
| 47 |
+
"num_hidden_layers": 28,
|
| 48 |
+
"num_key_value_heads": 2,
|
| 49 |
+
"pad_token_id": 151643,
|
| 50 |
+
"quantization_config": {
|
| 51 |
+
"bits": 4,
|
| 52 |
+
"checkpoint_format": "gptq",
|
| 53 |
+
"desc_act": false,
|
| 54 |
+
"format": "gptq",
|
| 55 |
+
"group_size": 128,
|
| 56 |
+
"lm_head": false,
|
| 57 |
+
"meta": {
|
| 58 |
+
"act_group_aware": true,
|
| 59 |
+
"auto_forward_data_parallel": true,
|
| 60 |
+
"damp_auto_increment": 0.01,
|
| 61 |
+
"damp_percent": 0.05,
|
| 62 |
+
"failsafe": {
|
| 63 |
+
"smooth": null,
|
| 64 |
+
"strategy": "rtn",
|
| 65 |
+
"threshold": "0.5%"
|
| 66 |
+
},
|
| 67 |
+
"gc_mode": "interval",
|
| 68 |
+
"gptaq": null,
|
| 69 |
+
"hessian": {
|
| 70 |
+
"chunk_bytes": null,
|
| 71 |
+
"chunk_size": null,
|
| 72 |
+
"staging_dtype": "float32"
|
| 73 |
+
},
|
| 74 |
+
"mock_quantization": false,
|
| 75 |
+
"mse": 0.0,
|
| 76 |
+
"offload_to_disk": true,
|
| 77 |
+
"offload_to_disk_path": "./gptqmodel_offload/vkhdvqgl-wrenvzpi/",
|
| 78 |
+
"pack_impl": "cpu",
|
| 79 |
+
"quantizer": [
|
| 80 |
+
"gptqmodel:5.8.0"
|
| 81 |
+
],
|
| 82 |
+
"static_groups": false,
|
| 83 |
+
"true_sequential": true,
|
| 84 |
+
"uri": "https://github.com/modelcloud/gptqmodel",
|
| 85 |
+
"vram_strategy": "exclusive",
|
| 86 |
+
"wait_for_submodule_finalizers": false
|
| 87 |
+
},
|
| 88 |
+
"pack_dtype": "int32",
|
| 89 |
+
"quant_method": "gptq",
|
| 90 |
+
"sym": true
|
| 91 |
+
},
|
| 92 |
+
"rms_norm_eps": 1e-06,
|
| 93 |
+
"rope_parameters": {
|
| 94 |
+
"rope_theta": 1000000.0,
|
| 95 |
+
"rope_type": "default"
|
| 96 |
+
},
|
| 97 |
+
"sliding_window": null,
|
| 98 |
+
"tie_word_embeddings": true,
|
| 99 |
+
"transformers_version": "5.4.0",
|
| 100 |
+
"use_cache": true,
|
| 101 |
+
"use_sliding_window": false,
|
| 102 |
+
"vocab_size": 151936
|
| 103 |
+
}
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generation_config.json
ADDED
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@@ -0,0 +1,13 @@
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{
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| 2 |
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"bos_token_id": 151643,
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| 3 |
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"do_sample": true,
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| 4 |
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"eos_token_id": [
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| 5 |
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151645,
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| 6 |
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151643
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| 7 |
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],
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| 8 |
+
"repetition_penalty": 1.1,
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| 9 |
+
"temperature": 0.7,
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| 10 |
+
"top_k": 20,
|
| 11 |
+
"top_p": 0.8,
|
| 12 |
+
"transformers_version": "5.4.0"
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| 13 |
+
}
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model.safetensors
ADDED
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:d48541182c22e9f9d688678b88e98c39633f4020799370e9e614d3953b5af035
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| 3 |
+
size 1149862904
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quant_log.csv
ADDED
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@@ -0,0 +1,197 @@
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|
| 1 |
+
layer,module,loss,samples,damp,time
|
| 2 |
+
0,self_attn.q_proj,0.0001942568,0.05000,3.519
|
| 3 |
+
0,self_attn.v_proj,0.0000033538,0.05000,3.620
|
| 4 |
+
0,self_attn.k_proj,0.0000293859,0.05000,3.614
|
| 5 |
+
0,self_attn.o_proj,0.0000074849,0.05000,0.828
|
| 6 |
+
0,mlp.gate_proj,0.0001148074,0.05000,1.608
|
| 7 |
+
0,mlp.up_proj,0.0000794248,0.05000,1.635
|
| 8 |
+
0,mlp.down_proj,0.0000133268,0.05000,4.222
|
| 9 |
+
1,self_attn.v_proj,0.0000021513,0.05000,3.167
|
| 10 |
+
1,self_attn.q_proj,0.0000325077,0.05000,3.201
|
| 11 |
+
1,self_attn.k_proj,0.0000094605,0.05000,3.233
|
| 12 |
+
1,self_attn.o_proj,0.0000030150,0.05000,0.610
|
| 13 |
+
1,mlp.gate_proj,0.0025643470,0.05000,1.753
|
| 14 |
+
1,mlp.up_proj,0.0020986227,0.05000,1.772
|
| 15 |
+
1,mlp.down_proj,0.0009006713,0.05000,3.821
|
| 16 |
+
2,self_attn.v_proj,0.0000084684,0.05000,3.665
|
| 17 |
+
2,self_attn.q_proj,0.0000954910,0.05000,3.666
|
| 18 |
+
2,self_attn.k_proj,0.0000202702,0.05000,3.718
|
| 19 |
+
2,self_attn.o_proj,0.0000040788,0.05000,0.575
|
| 20 |
+
2,mlp.gate_proj,0.0021059955,0.05000,1.774
|
| 21 |
+
2,mlp.up_proj,0.0013822045,0.05000,1.819
|
| 22 |
+
2,mlp.down_proj,0.0008856719,0.05000,3.623
|
| 23 |
+
3,self_attn.q_proj,0.0000963069,0.05000,3.376
|
| 24 |
+
3,self_attn.k_proj,0.0000205040,0.05000,3.453
|
| 25 |
+
3,self_attn.v_proj,0.0000115286,0.05000,3.487
|
| 26 |
+
3,self_attn.o_proj,0.0000066182,0.05000,0.693
|
| 27 |
+
3,mlp.gate_proj,0.0016237398,0.05000,1.920
|
| 28 |
+
3,mlp.up_proj,0.0008927437,0.05000,1.933
|
| 29 |
+
3,mlp.down_proj,0.0000440674,0.05000,3.765
|
| 30 |
+
4,self_attn.k_proj,0.0000238032,0.05000,3.398
|
| 31 |
+
4,self_attn.q_proj,0.0001242649,0.05000,3.501
|
| 32 |
+
4,self_attn.v_proj,0.0000161745,0.05000,3.530
|
| 33 |
+
4,self_attn.o_proj,0.0000089664,0.05000,0.618
|
| 34 |
+
4,mlp.gate_proj,0.0010840711,0.05000,1.829
|
| 35 |
+
4,mlp.up_proj,0.0006642618,0.05000,1.856
|
| 36 |
+
4,mlp.down_proj,0.0000501768,0.05000,3.848
|
| 37 |
+
5,self_attn.v_proj,0.0000227581,0.05000,3.174
|
| 38 |
+
5,self_attn.q_proj,0.0001299048,0.05000,3.270
|
| 39 |
+
5,self_attn.k_proj,0.0000275618,0.05000,3.280
|
| 40 |
+
5,self_attn.o_proj,0.0000138769,0.05000,0.670
|
| 41 |
+
5,mlp.up_proj,0.0013722564,0.05000,1.851
|
| 42 |
+
5,mlp.gate_proj,0.0020988442,0.05000,1.863
|
| 43 |
+
5,mlp.down_proj,0.0000409705,0.05000,4.404
|
| 44 |
+
6,self_attn.v_proj,0.0000188698,0.05000,3.315
|
| 45 |
+
6,self_attn.q_proj,0.0001721964,0.05000,3.351
|
| 46 |
+
6,self_attn.k_proj,0.0000359508,0.05000,3.383
|
| 47 |
+
6,self_attn.o_proj,0.0000058918,0.05000,0.593
|
| 48 |
+
6,mlp.gate_proj,0.0005833350,0.05000,1.583
|
| 49 |
+
6,mlp.up_proj,0.0004894385,0.05000,1.611
|
| 50 |
+
6,mlp.down_proj,0.0000467236,0.05000,3.904
|
| 51 |
+
7,self_attn.v_proj,0.0000124919,0.05000,3.632
|
| 52 |
+
7,self_attn.q_proj,0.0000809716,0.05000,3.632
|
| 53 |
+
7,self_attn.k_proj,0.0000157959,0.05000,3.803
|
| 54 |
+
7,self_attn.o_proj,0.0000089062,0.05000,0.716
|
| 55 |
+
7,mlp.up_proj,0.0004703383,0.05000,1.955
|
| 56 |
+
7,mlp.gate_proj,0.0004911946,0.05000,1.972
|
| 57 |
+
7,mlp.down_proj,0.0000479692,0.05000,4.039
|
| 58 |
+
8,self_attn.q_proj,0.0001606633,0.05000,3.426
|
| 59 |
+
8,self_attn.k_proj,0.0000285278,0.05000,3.517
|
| 60 |
+
8,self_attn.v_proj,0.0000176461,0.05000,3.571
|
| 61 |
+
8,self_attn.o_proj,0.0000114544,0.05000,0.660
|
| 62 |
+
8,mlp.gate_proj,0.0004976164,0.05000,2.604
|
| 63 |
+
8,mlp.up_proj,0.0004567402,0.05000,2.623
|
| 64 |
+
8,mlp.down_proj,0.0000424818,0.05000,4.143
|
| 65 |
+
9,self_attn.v_proj,0.0000145518,0.05000,3.436
|
| 66 |
+
9,self_attn.q_proj,0.0001237559,0.05000,3.441
|
| 67 |
+
9,self_attn.k_proj,0.0000253094,0.05000,3.456
|
| 68 |
+
9,self_attn.o_proj,0.0000114307,0.05000,0.677
|
| 69 |
+
9,mlp.gate_proj,0.0004502635,0.05000,1.684
|
| 70 |
+
9,mlp.up_proj,0.0004355869,0.05000,1.763
|
| 71 |
+
9,mlp.down_proj,0.0000410696,0.05000,3.787
|
| 72 |
+
10,self_attn.v_proj,0.0000207346,0.05000,4.259
|
| 73 |
+
10,self_attn.k_proj,0.0000242412,0.05000,4.348
|
| 74 |
+
10,self_attn.q_proj,0.0001243170,0.05000,4.352
|
| 75 |
+
10,self_attn.o_proj,0.0000184077,0.05000,0.714
|
| 76 |
+
10,mlp.gate_proj,0.0004360236,0.05000,2.063
|
| 77 |
+
10,mlp.up_proj,0.0004101034,0.05000,2.141
|
| 78 |
+
10,mlp.down_proj,0.0000363149,0.05000,3.978
|
| 79 |
+
11,self_attn.q_proj,0.0001229121,0.05000,3.551
|
| 80 |
+
11,self_attn.v_proj,0.0000171363,0.05000,3.682
|
| 81 |
+
11,self_attn.k_proj,0.0000240140,0.05000,3.698
|
| 82 |
+
11,self_attn.o_proj,0.0000168354,0.05000,0.696
|
| 83 |
+
11,mlp.gate_proj,0.0004277187,0.05000,1.717
|
| 84 |
+
11,mlp.up_proj,0.0003753171,0.05000,1.802
|
| 85 |
+
11,mlp.down_proj,0.0000307441,0.05000,3.849
|
| 86 |
+
12,self_attn.v_proj,0.0000160176,0.05000,3.036
|
| 87 |
+
12,self_attn.k_proj,0.0000313926,0.05000,3.061
|
| 88 |
+
12,self_attn.q_proj,0.0001444434,0.05000,3.129
|
| 89 |
+
12,self_attn.o_proj,0.0000115865,0.05000,0.586
|
| 90 |
+
12,mlp.up_proj,0.0003572416,0.05000,1.614
|
| 91 |
+
12,mlp.gate_proj,0.0003940164,0.05000,1.674
|
| 92 |
+
12,mlp.down_proj,0.0000321534,0.05000,3.836
|
| 93 |
+
13,self_attn.k_proj,0.0000188857,0.05000,3.238
|
| 94 |
+
13,self_attn.q_proj,0.0000945165,0.05000,3.262
|
| 95 |
+
13,self_attn.v_proj,0.0000123991,0.05000,3.287
|
| 96 |
+
13,self_attn.o_proj,0.0000148398,0.05000,0.745
|
| 97 |
+
13,mlp.up_proj,0.0003421897,0.05000,1.722
|
| 98 |
+
13,mlp.gate_proj,0.0003560762,0.05000,1.794
|
| 99 |
+
13,mlp.down_proj,0.0000275840,0.05000,4.004
|
| 100 |
+
14,self_attn.v_proj,0.0000249311,0.05000,3.388
|
| 101 |
+
14,self_attn.q_proj,0.0002223736,0.05000,3.478
|
| 102 |
+
14,self_attn.k_proj,0.0000331152,0.05000,3.506
|
| 103 |
+
14,self_attn.o_proj,0.0000111160,0.05000,0.599
|
| 104 |
+
14,mlp.gate_proj,0.0003798449,0.05000,1.741
|
| 105 |
+
14,mlp.up_proj,0.0003853373,0.05000,1.800
|
| 106 |
+
14,mlp.down_proj,0.0000325325,0.05000,4.420
|
| 107 |
+
15,self_attn.k_proj,0.0000236891,0.05000,3.697
|
| 108 |
+
15,self_attn.v_proj,0.0000209465,0.05000,3.741
|
| 109 |
+
15,self_attn.q_proj,0.0002121266,0.05000,3.752
|
| 110 |
+
15,self_attn.o_proj,0.0000193666,0.05000,0.624
|
| 111 |
+
15,mlp.gate_proj,0.0003494259,0.05000,1.794
|
| 112 |
+
15,mlp.up_proj,0.0003297445,0.05000,1.827
|
| 113 |
+
15,mlp.down_proj,0.0000274264,0.05000,4.004
|
| 114 |
+
16,self_attn.k_proj,0.0000308558,0.05000,3.403
|
| 115 |
+
16,self_attn.v_proj,0.0000237038,0.05000,3.440
|
| 116 |
+
16,self_attn.q_proj,0.0001626623,0.05000,3.475
|
| 117 |
+
16,self_attn.o_proj,0.0000150444,0.05000,0.622
|
| 118 |
+
16,mlp.gate_proj,0.0003889125,0.05000,1.860
|
| 119 |
+
16,mlp.up_proj,0.0003813872,0.05000,1.896
|
| 120 |
+
16,mlp.down_proj,0.0000318470,0.05000,4.405
|
| 121 |
+
17,self_attn.q_proj,0.0001462495,0.05000,3.408
|
| 122 |
+
17,self_attn.v_proj,0.0000311132,0.05000,3.492
|
| 123 |
+
17,self_attn.k_proj,0.0000180292,0.05000,3.489
|
| 124 |
+
17,self_attn.o_proj,0.0000120925,0.05000,0.696
|
| 125 |
+
17,mlp.gate_proj,0.0003979664,0.05000,2.337
|
| 126 |
+
17,mlp.up_proj,0.0003952374,0.05000,2.380
|
| 127 |
+
17,mlp.down_proj,0.0000415275,0.05000,3.937
|
| 128 |
+
18,self_attn.q_proj,0.0001291138,0.05000,3.377
|
| 129 |
+
18,self_attn.k_proj,0.0000215902,0.05000,3.553
|
| 130 |
+
18,self_attn.v_proj,0.0000218364,0.05000,3.576
|
| 131 |
+
18,self_attn.o_proj,0.0000215382,0.05000,0.656
|
| 132 |
+
18,mlp.gate_proj,0.0004375501,0.05000,1.857
|
| 133 |
+
18,mlp.up_proj,0.0004303935,0.05000,1.867
|
| 134 |
+
18,mlp.down_proj,0.0000551119,0.05000,4.582
|
| 135 |
+
19,self_attn.v_proj,0.0000468919,0.05000,3.290
|
| 136 |
+
19,self_attn.q_proj,0.0001769957,0.05000,3.319
|
| 137 |
+
19,self_attn.k_proj,0.0000234716,0.05000,3.392
|
| 138 |
+
19,self_attn.o_proj,0.0000198349,0.05000,0.578
|
| 139 |
+
19,mlp.gate_proj,0.0004960430,0.05000,2.169
|
| 140 |
+
19,mlp.up_proj,0.0005314743,0.05000,2.238
|
| 141 |
+
19,mlp.down_proj,0.0001041916,0.05000,4.563
|
| 142 |
+
20,self_attn.k_proj,0.0000279328,0.05000,3.557
|
| 143 |
+
20,self_attn.q_proj,0.0002208864,0.05000,3.645
|
| 144 |
+
20,self_attn.v_proj,0.0000660211,0.05000,3.669
|
| 145 |
+
20,self_attn.o_proj,0.0000338332,0.05000,0.588
|
| 146 |
+
20,mlp.up_proj,0.0005629465,0.05000,1.994
|
| 147 |
+
20,mlp.gate_proj,0.0005495163,0.05000,1.995
|
| 148 |
+
20,mlp.down_proj,0.0000975834,0.05000,4.368
|
| 149 |
+
21,self_attn.v_proj,0.0000588163,0.05000,3.694
|
| 150 |
+
21,self_attn.q_proj,0.0002200743,0.05000,3.721
|
| 151 |
+
21,self_attn.k_proj,0.0000272952,0.05000,3.829
|
| 152 |
+
21,self_attn.o_proj,0.0000264764,0.05000,0.686
|
| 153 |
+
21,mlp.gate_proj,0.0007878635,0.05000,2.148
|
| 154 |
+
21,mlp.up_proj,0.0007888174,0.05000,2.247
|
| 155 |
+
21,mlp.down_proj,0.0001698532,0.05000,3.959
|
| 156 |
+
22,self_attn.q_proj,0.0002093418,0.05000,3.808
|
| 157 |
+
22,self_attn.k_proj,0.0000318649,0.05000,3.851
|
| 158 |
+
22,self_attn.v_proj,0.0000711933,0.05000,3.869
|
| 159 |
+
22,self_attn.o_proj,0.0000268098,0.05000,0.768
|
| 160 |
+
22,mlp.gate_proj,0.0009505198,0.05000,1.796
|
| 161 |
+
22,mlp.up_proj,0.0009412312,0.05000,1.825
|
| 162 |
+
22,mlp.down_proj,0.0002310233,0.05000,4.523
|
| 163 |
+
23,self_attn.v_proj,0.0001066141,0.05000,4.407
|
| 164 |
+
23,self_attn.q_proj,0.0003122848,0.05000,4.404
|
| 165 |
+
23,self_attn.k_proj,0.0000369567,0.05000,4.458
|
| 166 |
+
23,self_attn.o_proj,0.0000279494,0.05000,0.759
|
| 167 |
+
23,mlp.up_proj,0.0010348070,0.05000,2.857
|
| 168 |
+
23,mlp.gate_proj,0.0009924937,0.05000,2.870
|
| 169 |
+
23,mlp.down_proj,0.0002910868,0.05000,5.011
|
| 170 |
+
24,self_attn.v_proj,0.0001675055,0.05000,3.922
|
| 171 |
+
24,self_attn.k_proj,0.0000384572,0.05000,4.003
|
| 172 |
+
24,self_attn.q_proj,0.0002870688,0.05000,4.012
|
| 173 |
+
24,self_attn.o_proj,0.0000425614,0.05000,0.735
|
| 174 |
+
24,mlp.up_proj,0.0011134829,0.05000,2.437
|
| 175 |
+
24,mlp.gate_proj,0.0010364587,0.05000,2.444
|
| 176 |
+
24,mlp.down_proj,0.0003481629,0.05000,4.686
|
| 177 |
+
25,self_attn.q_proj,0.0003447584,0.05000,4.070
|
| 178 |
+
25,self_attn.k_proj,0.0000364399,0.05000,4.078
|
| 179 |
+
25,self_attn.v_proj,0.0001667999,0.05000,4.065
|
| 180 |
+
25,self_attn.o_proj,0.0000568331,0.05000,0.845
|
| 181 |
+
25,mlp.gate_proj,0.0010463374,0.05000,1.863
|
| 182 |
+
25,mlp.up_proj,0.0012092180,0.05000,1.966
|
| 183 |
+
25,mlp.down_proj,0.0004537338,0.05000,4.291
|
| 184 |
+
26,self_attn.v_proj,0.0002388664,0.05000,3.937
|
| 185 |
+
26,self_attn.q_proj,0.0003158843,0.05000,4.007
|
| 186 |
+
26,self_attn.k_proj,0.0000400289,0.05000,4.045
|
| 187 |
+
26,self_attn.o_proj,0.0000527040,0.05000,0.690
|
| 188 |
+
26,mlp.up_proj,0.0012510429,0.05000,2.057
|
| 189 |
+
26,mlp.gate_proj,0.0010409112,0.05000,2.327
|
| 190 |
+
26,mlp.down_proj,0.0020226345,0.05000,4.384
|
| 191 |
+
27,self_attn.v_proj,0.0002370400,0.05000,4.069
|
| 192 |
+
27,self_attn.q_proj,0.0003039186,0.05000,4.089
|
| 193 |
+
27,self_attn.k_proj,0.0000327215,0.05000,4.103
|
| 194 |
+
27,self_attn.o_proj,0.0001643453,0.05000,0.791
|
| 195 |
+
27,mlp.gate_proj,0.0015339861,0.05000,2.210
|
| 196 |
+
27,mlp.up_proj,0.0015848841,0.05000,2.267
|
| 197 |
+
27,mlp.down_proj,0.0012275284,0.05000,4.896
|
quantize_config.json
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bits": 4,
|
| 3 |
+
"group_size": 128,
|
| 4 |
+
"desc_act": false,
|
| 5 |
+
"sym": true,
|
| 6 |
+
"quant_method": "gptq"
|
| 7 |
+
}
|
quantize_manifest.json
ADDED
|
@@ -0,0 +1,12 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"model_name": "qwen2.5-1.5b",
|
| 3 |
+
"hf_id": "Qwen/Qwen2.5-1.5B-Instruct",
|
| 4 |
+
"method": "gptq",
|
| 5 |
+
"bits": 4,
|
| 6 |
+
"group_size": 128,
|
| 7 |
+
"calibration_dataset": "allenai/c4",
|
| 8 |
+
"calibration_samples": 128,
|
| 9 |
+
"seed": 42,
|
| 10 |
+
"elapsed_s": 554.7059471607208,
|
| 11 |
+
"tool": "gptqmodel"
|
| 12 |
+
}
|
tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3fd169731d2cbde95e10bf356d66d5997fd885dd8dbb6fb4684da3f23b2585d8
|
| 3 |
+
size 11421892
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,30 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"backend": "tokenizers",
|
| 4 |
+
"bos_token": null,
|
| 5 |
+
"clean_up_tokenization_spaces": false,
|
| 6 |
+
"eos_token": "<|im_end|>",
|
| 7 |
+
"errors": "replace",
|
| 8 |
+
"extra_special_tokens": {
|
| 9 |
+
"<|im_start|>": "<|im_start|>",
|
| 10 |
+
"<|im_end|>": "<|im_end|>",
|
| 11 |
+
"<|object_ref_start|>": "<|object_ref_start|>",
|
| 12 |
+
"<|object_ref_end|>": "<|object_ref_end|>",
|
| 13 |
+
"<|box_start|>": "<|box_start|>",
|
| 14 |
+
"<|box_end|>": "<|box_end|>",
|
| 15 |
+
"<|quad_start|>": "<|quad_start|>",
|
| 16 |
+
"<|quad_end|>": "<|quad_end|>",
|
| 17 |
+
"<|vision_start|>": "<|vision_start|>",
|
| 18 |
+
"<|vision_end|>": "<|vision_end|>",
|
| 19 |
+
"<|vision_pad|>": "<|vision_pad|>",
|
| 20 |
+
"<|image_pad|>": "<|image_pad|>",
|
| 21 |
+
"<|video_pad|>": "<|video_pad|>"
|
| 22 |
+
},
|
| 23 |
+
"is_local": false,
|
| 24 |
+
"model_max_length": 131072,
|
| 25 |
+
"pad_token": "<|endoftext|>",
|
| 26 |
+
"split_special_tokens": false,
|
| 27 |
+
"tokenizer_class": "Qwen2TokenizerFast",
|
| 28 |
+
"unk_token": null,
|
| 29 |
+
"_commit_hash": null
|
| 30 |
+
}
|