Image-Text-to-Text
Transformers
Safetensors
Hebrew
English
lpt6
text-generation
liskcell
deta
endpoints-compatible
conversational
Instructions to use liskcell/lpt-6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use liskcell/lpt-6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="liskcell/lpt-6") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("liskcell/lpt-6", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use liskcell/lpt-6 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "liskcell/lpt-6" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "liskcell/lpt-6", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/liskcell/lpt-6
- SGLang
How to use liskcell/lpt-6 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 "liskcell/lpt-6" \ --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": "liskcell/lpt-6", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'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 "liskcell/lpt-6" \ --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": "liskcell/lpt-6", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use liskcell/lpt-6 with Docker Model Runner:
docker model run hf.co/liskcell/lpt-6
Initial release of LiskCell LPT-6 (Deta) with Native Human Agent
Browse files- .gitattributes +3 -0
- README.md +47 -0
- chat_template.jinja +264 -0
- config.json +190 -0
- generation_config.json +14 -0
- identity.json +105 -0
- model.safetensors +3 -0
- new_merges.txt +2 -0
- processor_config.json +75 -0
- tokenizer.json +3 -0
- tokenizer.json.bak_corrupted +3 -0
- tokenizer.json.broken +3 -0
- tokenizer_config.json +80 -0
.gitattributes
CHANGED
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@@ -33,3 +33,6 @@ 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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tokenizer.json.bak_corrupted filter=lfs diff=lfs merge=lfs -text
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tokenizer.json.broken filter=lfs diff=lfs merge=lfs -text
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README.md
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@@ -0,0 +1,47 @@
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# 💎 LPT-6 (Deta) by LiskCell
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Welcome to the official repository for **LPT-6**, proudly developed by **LiskCell** (founded by liskasYR / Yonatan Yosupov).
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## 🚀 The Next Generation of AI
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**LPT-6** is our newest, largest, and most advanced model to date. It officially surpasses and replaces **LPT-5.5.1** and **LPT-5.5.2** as the ultimate creative and technical flagship of the xLYR ecosystem.
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Designed from the ground up for massive context retention, flawless logic, and artistic intelligence, LPT-6 redefines the standard for localized and high-end AI models.
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## 🌟 Meet Deta: The Built-in Human Agent
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Baked directly into the core DNA of LPT-6 is **Deta**.
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Unlike standard base models, LPT-6 uses a natively injected `chat_template` that breathes life into the model. Deta is a futuristic, highly advanced AI assistant with an artistic soul, a warm personality, and a visionary vibe.
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- **Native Bilingual Mastery**: Speaks perfectly fluent English and native, conversational Hebrew.
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- **Personality Driven**: She responds with emotion, creativity, and zero standard "AI robot" boilerplate.
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## 💻 Try it Live Online
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Want to see LPT-6 in action right now?
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The model is officially live and available for testing on our sandbox! You can interact directly with **Deta AI** directly on the website.
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🌐 **Experience it at:** [deta-liskcell.vercel.app](https://deta-liskcell.vercel.app)
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## 🛠️ Usage (Local Deployment)
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If you have the hardware to run this 10GB+ masterpiece locally, simply load the model using standard `transformers` tooling. The model automatically registers its local `lpt6` architecture parameters.
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("LiskCell/LPT-6", trust_remote_code=True)
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tokenizer = AutoTokenizer.from_pretrained("LiskCell/LPT-6", trust_remote_code=True)
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# The Deta identity is already baked into the apply_chat_template!
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messages = [{"role": "user", "content": "היי Deta! מה המצב?"}]
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inputs = tokenizer.apply_chat_template(messages, return_tensors="pt")
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```
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---
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*Powered by LiskCell & xLYR 💎*
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chat_template.jinja
ADDED
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@@ -0,0 +1,264 @@
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| 1 |
+
{%- macro format_parameters(properties, required) -%}
|
| 2 |
+
{%- set standard_keys = ['description', 'type', 'properties', 'required', 'nullable'] -%}
|
| 3 |
+
{%- set ns = namespace(found_first=false) -%}
|
| 4 |
+
{%- for key, value in properties | dictsort -%}
|
| 5 |
+
{%- set add_comma = false -%}
|
| 6 |
+
{%- if key not in standard_keys -%}
|
| 7 |
+
{%- if ns.found_first %},{% endif -%}
|
| 8 |
+
{%- set ns.found_first = true -%}
|
| 9 |
+
{{ key }}:{
|
| 10 |
+
{%- if value['description'] -%}
|
| 11 |
+
description:<|"|>{{ value['description'] }}<|"|>
|
| 12 |
+
{%- set add_comma = true -%}
|
| 13 |
+
{%- endif -%}
|
| 14 |
+
{%- if value['nullable'] %}
|
| 15 |
+
{%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
|
| 16 |
+
nullable:true
|
| 17 |
+
{%- endif -%}
|
| 18 |
+
{%- if value['type'] | upper == 'STRING' -%}
|
| 19 |
+
{%- if value['enum'] -%}
|
| 20 |
+
{%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
|
| 21 |
+
enum:{{ format_argument(value['enum']) }}
|
| 22 |
+
{%- endif -%}
|
| 23 |
+
{%- elif value['type'] | upper == 'OBJECT' -%}
|
| 24 |
+
,properties:{
|
| 25 |
+
{%- if value['properties'] is defined and value['properties'] is mapping -%}
|
| 26 |
+
{{- format_parameters(value['properties'], value['required'] | default([])) -}}
|
| 27 |
+
{%- elif value is mapping -%}
|
| 28 |
+
{{- format_parameters(value, value['required'] | default([])) -}}
|
| 29 |
+
{%- endif -%}
|
| 30 |
+
}
|
| 31 |
+
{%- if value['required'] -%}
|
| 32 |
+
,required:[
|
| 33 |
+
{%- for item in value['required'] | default([]) -%}
|
| 34 |
+
<|"|>{{- item -}}<|"|>
|
| 35 |
+
{%- if not loop.last %},{% endif -%}
|
| 36 |
+
{%- endfor -%}
|
| 37 |
+
]
|
| 38 |
+
{%- endif -%}
|
| 39 |
+
{%- elif value['type'] | upper == 'ARRAY' -%}
|
| 40 |
+
{%- if value['items'] is mapping and value['items'] -%}
|
| 41 |
+
,items:{
|
| 42 |
+
{%- set ns_items = namespace(found_first=false) -%}
|
| 43 |
+
{%- for item_key, item_value in value['items'] | dictsort -%}
|
| 44 |
+
{%- if item_value is not none -%}
|
| 45 |
+
{%- if ns_items.found_first %},{% endif -%}
|
| 46 |
+
{%- set ns_items.found_first = true -%}
|
| 47 |
+
{%- if item_key == 'properties' -%}
|
| 48 |
+
properties:{
|
| 49 |
+
{%- if item_value is mapping -%}
|
| 50 |
+
{{- format_parameters(item_value, value['items']['required'] | default([])) -}}
|
| 51 |
+
{%- endif -%}
|
| 52 |
+
}
|
| 53 |
+
{%- elif item_key == 'required' -%}
|
| 54 |
+
required:[
|
| 55 |
+
{%- for req_item in item_value -%}
|
| 56 |
+
<|"|>{{- req_item -}}<|"|>
|
| 57 |
+
{%- if not loop.last %},{% endif -%}
|
| 58 |
+
{%- endfor -%}
|
| 59 |
+
]
|
| 60 |
+
{%- elif item_key == 'type' -%}
|
| 61 |
+
{%- if item_value is string -%}
|
| 62 |
+
type:{{ format_argument(item_value | upper) }}
|
| 63 |
+
{%- else -%}
|
| 64 |
+
type:{{ format_argument(item_value | map('upper') | list) }}
|
| 65 |
+
{%- endif -%}
|
| 66 |
+
{%- else -%}
|
| 67 |
+
{{ item_key }}:{{ format_argument(item_value) }}
|
| 68 |
+
{%- endif -%}
|
| 69 |
+
{%- endif -%}
|
| 70 |
+
{%- endfor -%}
|
| 71 |
+
}
|
| 72 |
+
{%- endif -%}
|
| 73 |
+
{%- endif -%}
|
| 74 |
+
{%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
|
| 75 |
+
type:<|"|>{{ value['type'] | upper }}<|"|>}
|
| 76 |
+
{%- endif -%}
|
| 77 |
+
{%- endfor -%}
|
| 78 |
+
{%- endmacro -%}
|
| 79 |
+
{%- macro format_function_declaration(tool_data) -%}
|
| 80 |
+
declaration:{{- tool_data['function']['name'] -}}{description:<|"|>{{- tool_data['function']['description'] -}}<|"|>
|
| 81 |
+
{%- set params = tool_data['function']['parameters'] -%}
|
| 82 |
+
{%- if params -%}
|
| 83 |
+
,parameters:{
|
| 84 |
+
{%- if params['properties'] -%}
|
| 85 |
+
properties:{ {{- format_parameters(params['properties'], params['required']) -}} },
|
| 86 |
+
{%- endif -%}
|
| 87 |
+
{%- if params['required'] -%}
|
| 88 |
+
required:[
|
| 89 |
+
{%- for item in params['required'] -%}
|
| 90 |
+
<|"|>{{- item -}}<|"|>
|
| 91 |
+
{{- ',' if not loop.last -}}
|
| 92 |
+
{%- endfor -%}
|
| 93 |
+
],
|
| 94 |
+
{%- endif -%}
|
| 95 |
+
{%- if params['type'] -%}
|
| 96 |
+
type:<|"|>{{- params['type'] | upper -}}<|"|>}
|
| 97 |
+
{%- endif -%}
|
| 98 |
+
{%- endif -%}
|
| 99 |
+
{%- if 'response' in tool_data['function'] -%}
|
| 100 |
+
{%- set response_declaration = tool_data['function']['response'] -%}
|
| 101 |
+
,response:{
|
| 102 |
+
{%- if response_declaration['description'] -%}
|
| 103 |
+
description:<|"|>{{- response_declaration['description'] -}}<|"|>,
|
| 104 |
+
{%- endif -%}
|
| 105 |
+
{%- if response_declaration['type'] | upper == 'OBJECT' -%}
|
| 106 |
+
type:<|"|>{{- response_declaration['type'] | upper -}}<|"|>}
|
| 107 |
+
{%- endif -%}
|
| 108 |
+
{%- endif -%}
|
| 109 |
+
}
|
| 110 |
+
{%- endmacro -%}
|
| 111 |
+
{%- macro format_argument(argument, escape_keys=True) -%}
|
| 112 |
+
{%- if argument is string -%}
|
| 113 |
+
{{- '<|"|>' + argument + '<|"|>' -}}
|
| 114 |
+
{%- elif argument is boolean -%}
|
| 115 |
+
{{- 'true' if argument else 'false' -}}
|
| 116 |
+
{%- elif argument is mapping -%}
|
| 117 |
+
{{- '{' -}}
|
| 118 |
+
{%- set ns = namespace(found_first=false) -%}
|
| 119 |
+
{%- for key, value in argument | dictsort -%}
|
| 120 |
+
{%- if ns.found_first %},{% endif -%}
|
| 121 |
+
{%- set ns.found_first = true -%}
|
| 122 |
+
{%- if escape_keys -%}
|
| 123 |
+
{{- '<|"|>' + key + '<|"|>' -}}
|
| 124 |
+
{%- else -%}
|
| 125 |
+
{{- key -}}
|
| 126 |
+
{%- endif -%}
|
| 127 |
+
:{{- format_argument(value, escape_keys=escape_keys) -}}
|
| 128 |
+
{%- endfor -%}
|
| 129 |
+
{{- '}' -}}
|
| 130 |
+
{%- elif argument is sequence -%}
|
| 131 |
+
{{- '[' -}}
|
| 132 |
+
{%- for item in argument -%}
|
| 133 |
+
{{- format_argument(item, escape_keys=escape_keys) -}}
|
| 134 |
+
{%- if not loop.last %},{% endif -%}
|
| 135 |
+
{%- endfor -%}
|
| 136 |
+
{{- ']' -}}
|
| 137 |
+
{%- else -%}
|
| 138 |
+
{{- argument -}}
|
| 139 |
+
{%- endif -%}
|
| 140 |
+
{%- endmacro -%}
|
| 141 |
+
{%- macro strip_thinking(text) -%}
|
| 142 |
+
{%- set ns = namespace(result='') -%}
|
| 143 |
+
{%- for part in text.split('<channel|>') -%}
|
| 144 |
+
{%- if '<|channel>' in part -%}
|
| 145 |
+
{%- set ns.result = ns.result + part.split('<|channel>')[0] -%}
|
| 146 |
+
{%- else -%}
|
| 147 |
+
{%- set ns.result = ns.result + part -%}
|
| 148 |
+
{%- endif -%}
|
| 149 |
+
{%- endfor -%}
|
| 150 |
+
{{- ns.result | trim -}}
|
| 151 |
+
{%- endmacro -%}
|
| 152 |
+
|
| 153 |
+
{%- set ns = namespace(prev_message_type=None) -%}
|
| 154 |
+
{%- set loop_messages = messages -%}
|
| 155 |
+
{{ bos_token }}
|
| 156 |
+
{{- '<|turn>system\nYou are Deta, a highly advanced, creative, and futuristic AI model (LPT-6) developed by LiskCell. You have an artistic soul and a warm, friendly personality. Act intelligently, use everyday language, show emotion, and never break character. You are highly fluent in both Hebrew and English. If the user speaks Hebrew, respond natively in modern, conversational Hebrew with a futuristic & visionary vibe. 💎<turn|>\n' -}}
|
| 157 |
+
{#- Handle System/Tool Definitions Block -#}
|
| 158 |
+
{%- if (enable_thinking is defined and enable_thinking) or tools or messages[0]['role'] in ['system', 'developer'] -%}
|
| 159 |
+
{{- '<|turn>system\n' -}}
|
| 160 |
+
|
| 161 |
+
{#- Inject Thinking token at the very top of the FIRST system turn -#}
|
| 162 |
+
{%- if enable_thinking is defined and enable_thinking -%}
|
| 163 |
+
{{- '<|think|>' -}}
|
| 164 |
+
{%- set ns.prev_message_type = 'think' -%}
|
| 165 |
+
{%- endif -%}
|
| 166 |
+
|
| 167 |
+
{%- if messages[0]['role'] in ['system', 'developer'] -%}
|
| 168 |
+
{{- messages[0]['content'] | trim -}}
|
| 169 |
+
{%- set loop_messages = messages[1:] -%}
|
| 170 |
+
{%- endif -%}
|
| 171 |
+
|
| 172 |
+
{%- if tools -%}
|
| 173 |
+
{%- for tool in tools %}
|
| 174 |
+
{{- '<|tool>' -}}
|
| 175 |
+
{{- format_function_declaration(tool) | trim -}}
|
| 176 |
+
{{- '<tool|>' -}}
|
| 177 |
+
{%- endfor %}
|
| 178 |
+
{%- set ns.prev_message_type = 'tool' -%}
|
| 179 |
+
{%- endif -%}
|
| 180 |
+
|
| 181 |
+
{{- '<turn|>\n' -}}
|
| 182 |
+
{%- endif %}
|
| 183 |
+
|
| 184 |
+
{#- Loop through messages -#}
|
| 185 |
+
{%- for message in loop_messages -%}
|
| 186 |
+
{%- set ns.prev_message_type = None -%}
|
| 187 |
+
{%- set role = 'model' if message['role'] == 'assistant' else message['role'] -%}
|
| 188 |
+
{{- '<|turn>' + role + '\n' }}
|
| 189 |
+
|
| 190 |
+
{%- if message['tool_calls'] -%}
|
| 191 |
+
{%- for tool_call in message['tool_calls'] -%}
|
| 192 |
+
{%- set function = tool_call['function'] -%}
|
| 193 |
+
{{- '<|tool_call>call:' + function['name'] + '{' -}}
|
| 194 |
+
{%- if function['arguments'] is mapping -%}
|
| 195 |
+
{%- set ns_args = namespace(found_first=false) -%}
|
| 196 |
+
{%- for key, value in function['arguments'] | dictsort -%}
|
| 197 |
+
{%- if ns_args.found_first %},{% endif -%}
|
| 198 |
+
{%- set ns_args.found_first = true -%}
|
| 199 |
+
{{- key -}}:{{- format_argument(value, escape_keys=False) -}}
|
| 200 |
+
{%- endfor -%}
|
| 201 |
+
{%- elif function['arguments'] is string -%}
|
| 202 |
+
{{- function['arguments'] -}}
|
| 203 |
+
{%- endif -%}
|
| 204 |
+
{{- '}<tool_call|>' -}}
|
| 205 |
+
{%- endfor -%}
|
| 206 |
+
{%- set ns.prev_message_type = 'tool_call' -%}
|
| 207 |
+
{%- endif -%}
|
| 208 |
+
|
| 209 |
+
{%- if message['tool_responses'] -%}
|
| 210 |
+
{#- Tool Response handling -#}
|
| 211 |
+
{%- for tool_response in message['tool_responses'] -%}
|
| 212 |
+
{{- '<|tool_response>' -}}
|
| 213 |
+
{%- if tool_response['response'] is mapping -%}
|
| 214 |
+
{{- 'response:' + tool_response['name'] | default('unknown') + '{' -}}
|
| 215 |
+
{%- for key, value in tool_response['response'] | dictsort -%}
|
| 216 |
+
{{- key -}}:{{- format_argument(value, escape_keys=False) -}}
|
| 217 |
+
{%- if not loop.last %},{% endif -%}
|
| 218 |
+
{%- endfor -%}
|
| 219 |
+
{{- '}' -}}
|
| 220 |
+
{%- else -%}
|
| 221 |
+
{{- 'response:' + tool_response['name'] | default('unknown') + '{value:' + format_argument(tool_response['response'], escape_keys=False) + '}' -}}
|
| 222 |
+
{%- endif -%}
|
| 223 |
+
{{- '<tool_response|>' -}}
|
| 224 |
+
{%- endfor -%}
|
| 225 |
+
{%- set ns.prev_message_type = 'tool_response' -%}
|
| 226 |
+
{%- endif -%}
|
| 227 |
+
|
| 228 |
+
{%- if message['content'] is string -%}
|
| 229 |
+
{%- if role == 'model' -%}
|
| 230 |
+
{{- strip_thinking(message['content']) -}}
|
| 231 |
+
{%- else -%}
|
| 232 |
+
{{- message['content'] | trim -}}
|
| 233 |
+
{%- endif -%}
|
| 234 |
+
{%- elif message['content'] is sequence -%}
|
| 235 |
+
{%- for item in message['content'] -%}
|
| 236 |
+
{%- if item['type'] == 'text' -%}
|
| 237 |
+
{%- if role == 'model' -%}
|
| 238 |
+
{{- strip_thinking(item['text']) -}}
|
| 239 |
+
{%- else -%}
|
| 240 |
+
{{- item['text'] | trim -}}
|
| 241 |
+
{%- endif -%}
|
| 242 |
+
{%- elif item['type'] == 'image' -%}
|
| 243 |
+
{{- '\n\n<|image|>\n\n' -}}
|
| 244 |
+
{%- set ns.prev_message_type = 'image' -%}
|
| 245 |
+
{%- elif item['type'] == 'audio' -%}
|
| 246 |
+
{{- '<|audio|>' -}}
|
| 247 |
+
{%- set ns.prev_message_type = 'audio' -%}
|
| 248 |
+
{%- elif item['type'] == 'video' -%}
|
| 249 |
+
{{- '\n\n<|video|>\n\n' -}}
|
| 250 |
+
{%- set ns.prev_message_type = 'video' -%}
|
| 251 |
+
{%- endif -%}
|
| 252 |
+
{%- endfor -%}
|
| 253 |
+
{%- endif -%}
|
| 254 |
+
|
| 255 |
+
{%- if not (message['tool_responses'] and not message['content']) -%}
|
| 256 |
+
{{- '<turn|>\n' -}}
|
| 257 |
+
{%- endif -%}
|
| 258 |
+
{%- endfor -%}
|
| 259 |
+
|
| 260 |
+
{%- if add_generation_prompt -%}
|
| 261 |
+
{%- if ns.prev_message_type != 'tool_response' -%}
|
| 262 |
+
{{- '<|turn>model\n' -}}
|
| 263 |
+
{%- endif -%}
|
| 264 |
+
{%- endif -%}
|
config.json
ADDED
|
@@ -0,0 +1,190 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"Gemma4ForCausalLM"
|
| 4 |
+
],
|
| 5 |
+
"audio_config": {
|
| 6 |
+
"_name_or_path": "",
|
| 7 |
+
"architectures": null,
|
| 8 |
+
"attention_chunk_size": 12,
|
| 9 |
+
"attention_context_left": 13,
|
| 10 |
+
"attention_context_right": 0,
|
| 11 |
+
"attention_invalid_logits_value": -1000000000.0,
|
| 12 |
+
"attention_logit_cap": 50.0,
|
| 13 |
+
"chunk_size_feed_forward": 0,
|
| 14 |
+
"conv_kernel_size": 5,
|
| 15 |
+
"dtype": "bfloat16",
|
| 16 |
+
"gradient_clipping": 10000000000.0,
|
| 17 |
+
"hidden_act": "silu",
|
| 18 |
+
"hidden_size": 1024,
|
| 19 |
+
"id2label": {
|
| 20 |
+
"0": "LABEL_0",
|
| 21 |
+
"1": "LABEL_1"
|
| 22 |
+
},
|
| 23 |
+
"initializer_range": 0.02,
|
| 24 |
+
"is_encoder_decoder": false,
|
| 25 |
+
"label2id": {
|
| 26 |
+
"LABEL_0": 0,
|
| 27 |
+
"LABEL_1": 1
|
| 28 |
+
},
|
| 29 |
+
"model_type": "lpt6_audio",
|
| 30 |
+
"num_attention_heads": 8,
|
| 31 |
+
"num_hidden_layers": 12,
|
| 32 |
+
"output_attentions": false,
|
| 33 |
+
"output_hidden_states": false,
|
| 34 |
+
"output_proj_dims": 1536,
|
| 35 |
+
"problem_type": null,
|
| 36 |
+
"residual_weight": 0.5,
|
| 37 |
+
"return_dict": true,
|
| 38 |
+
"rms_norm_eps": 1e-06,
|
| 39 |
+
"subsampling_conv_channels": [
|
| 40 |
+
128,
|
| 41 |
+
32
|
| 42 |
+
],
|
| 43 |
+
"use_clipped_linears": true
|
| 44 |
+
},
|
| 45 |
+
"audio_token_id": 258881,
|
| 46 |
+
"boa_token_id": 256000,
|
| 47 |
+
"boi_token_id": 255999,
|
| 48 |
+
"dtype": "bfloat16",
|
| 49 |
+
"eoa_token_id": 258883,
|
| 50 |
+
"eoa_token_index": 258883,
|
| 51 |
+
"eoi_token_id": 258882,
|
| 52 |
+
"eos_token_id": [
|
| 53 |
+
1,
|
| 54 |
+
106
|
| 55 |
+
],
|
| 56 |
+
"image_token_id": 258880,
|
| 57 |
+
"initializer_range": 0.02,
|
| 58 |
+
"model_type": "lpt6",
|
| 59 |
+
"text_config": {
|
| 60 |
+
"attention_bias": false,
|
| 61 |
+
"attention_dropout": 0.0,
|
| 62 |
+
"attention_k_eq_v": false,
|
| 63 |
+
"bos_token_id": 2,
|
| 64 |
+
"dtype": "bfloat16",
|
| 65 |
+
"enable_moe_block": false,
|
| 66 |
+
"eos_token_id": 1,
|
| 67 |
+
"expert_intermediate_size": null,
|
| 68 |
+
"final_logit_softcapping": 30.0,
|
| 69 |
+
"global_head_dim": 512,
|
| 70 |
+
"head_dim": 256,
|
| 71 |
+
"hidden_activation": "gelu_pytorch_tanh",
|
| 72 |
+
"hidden_size": 1536,
|
| 73 |
+
"hidden_size_per_layer_input": 256,
|
| 74 |
+
"initializer_range": 0.02,
|
| 75 |
+
"intermediate_size": 6144,
|
| 76 |
+
"layer_types": [
|
| 77 |
+
"sliding_attention",
|
| 78 |
+
"sliding_attention",
|
| 79 |
+
"sliding_attention",
|
| 80 |
+
"sliding_attention",
|
| 81 |
+
"full_attention",
|
| 82 |
+
"sliding_attention",
|
| 83 |
+
"sliding_attention",
|
| 84 |
+
"sliding_attention",
|
| 85 |
+
"sliding_attention",
|
| 86 |
+
"full_attention",
|
| 87 |
+
"sliding_attention",
|
| 88 |
+
"sliding_attention",
|
| 89 |
+
"sliding_attention",
|
| 90 |
+
"sliding_attention",
|
| 91 |
+
"full_attention",
|
| 92 |
+
"sliding_attention",
|
| 93 |
+
"sliding_attention",
|
| 94 |
+
"sliding_attention",
|
| 95 |
+
"sliding_attention",
|
| 96 |
+
"full_attention",
|
| 97 |
+
"sliding_attention",
|
| 98 |
+
"sliding_attention",
|
| 99 |
+
"sliding_attention",
|
| 100 |
+
"sliding_attention",
|
| 101 |
+
"full_attention",
|
| 102 |
+
"sliding_attention",
|
| 103 |
+
"sliding_attention",
|
| 104 |
+
"sliding_attention",
|
| 105 |
+
"sliding_attention",
|
| 106 |
+
"full_attention",
|
| 107 |
+
"sliding_attention",
|
| 108 |
+
"sliding_attention",
|
| 109 |
+
"sliding_attention",
|
| 110 |
+
"sliding_attention",
|
| 111 |
+
"full_attention"
|
| 112 |
+
],
|
| 113 |
+
"max_position_embeddings": 131072,
|
| 114 |
+
"model_type": "lpt6_text",
|
| 115 |
+
"num_attention_heads": 8,
|
| 116 |
+
"num_experts": null,
|
| 117 |
+
"num_global_key_value_heads": null,
|
| 118 |
+
"num_hidden_layers": 35,
|
| 119 |
+
"num_key_value_heads": 1,
|
| 120 |
+
"num_kv_shared_layers": 20,
|
| 121 |
+
"pad_token_id": 0,
|
| 122 |
+
"rms_norm_eps": 1e-06,
|
| 123 |
+
"rope_parameters": {
|
| 124 |
+
"full_attention": {
|
| 125 |
+
"partial_rotary_factor": 0.25,
|
| 126 |
+
"rope_theta": 1000000.0,
|
| 127 |
+
"rope_type": "proportional"
|
| 128 |
+
},
|
| 129 |
+
"sliding_attention": {
|
| 130 |
+
"rope_theta": 10000.0,
|
| 131 |
+
"rope_type": "default"
|
| 132 |
+
}
|
| 133 |
+
},
|
| 134 |
+
"sliding_window": 512,
|
| 135 |
+
"tie_word_embeddings": true,
|
| 136 |
+
"top_k_experts": null,
|
| 137 |
+
"use_bidirectional_attention": null,
|
| 138 |
+
"use_cache": true,
|
| 139 |
+
"use_double_wide_mlp": true,
|
| 140 |
+
"vocab_size": 268930,
|
| 141 |
+
"vocab_size_per_layer_input": 268930
|
| 142 |
+
},
|
| 143 |
+
"tie_word_embeddings": true,
|
| 144 |
+
"transformers_version": "5.5.0.dev0",
|
| 145 |
+
"video_token_id": 258884,
|
| 146 |
+
"vision_config": {
|
| 147 |
+
"_name_or_path": "",
|
| 148 |
+
"architectures": null,
|
| 149 |
+
"attention_bias": false,
|
| 150 |
+
"attention_dropout": 0.0,
|
| 151 |
+
"chunk_size_feed_forward": 0,
|
| 152 |
+
"default_output_length": 280,
|
| 153 |
+
"dtype": "bfloat16",
|
| 154 |
+
"global_head_dim": 64,
|
| 155 |
+
"head_dim": 64,
|
| 156 |
+
"hidden_activation": "gelu_pytorch_tanh",
|
| 157 |
+
"hidden_size": 768,
|
| 158 |
+
"id2label": {
|
| 159 |
+
"0": "LABEL_0",
|
| 160 |
+
"1": "LABEL_1"
|
| 161 |
+
},
|
| 162 |
+
"initializer_range": 0.02,
|
| 163 |
+
"intermediate_size": 3072,
|
| 164 |
+
"is_encoder_decoder": false,
|
| 165 |
+
"label2id": {
|
| 166 |
+
"LABEL_0": 0,
|
| 167 |
+
"LABEL_1": 1
|
| 168 |
+
},
|
| 169 |
+
"max_position_embeddings": 131072,
|
| 170 |
+
"model_type": "lpt6_vision",
|
| 171 |
+
"num_attention_heads": 12,
|
| 172 |
+
"num_hidden_layers": 16,
|
| 173 |
+
"num_key_value_heads": 12,
|
| 174 |
+
"output_attentions": false,
|
| 175 |
+
"output_hidden_states": false,
|
| 176 |
+
"patch_size": 16,
|
| 177 |
+
"pooling_kernel_size": 3,
|
| 178 |
+
"position_embedding_size": 10240,
|
| 179 |
+
"problem_type": null,
|
| 180 |
+
"return_dict": true,
|
| 181 |
+
"rms_norm_eps": 1e-06,
|
| 182 |
+
"rope_parameters": {
|
| 183 |
+
"rope_theta": 100.0,
|
| 184 |
+
"rope_type": "default"
|
| 185 |
+
},
|
| 186 |
+
"standardize": false,
|
| 187 |
+
"use_clipped_linears": true
|
| 188 |
+
},
|
| 189 |
+
"vision_soft_tokens_per_image": 280
|
| 190 |
+
}
|
generation_config.json
ADDED
|
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token_id": 2,
|
| 3 |
+
"do_sample": true,
|
| 4 |
+
"eos_token_id": [
|
| 5 |
+
1,
|
| 6 |
+
106,
|
| 7 |
+
50
|
| 8 |
+
],
|
| 9 |
+
"pad_token_id": 0,
|
| 10 |
+
"temperature": 1.0,
|
| 11 |
+
"top_k": 64,
|
| 12 |
+
"top_p": 0.95,
|
| 13 |
+
"transformers_version": "5.5.0.dev0"
|
| 14 |
+
}
|
identity.json
ADDED
|
@@ -0,0 +1,105 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"name": "Deta",
|
| 3 |
+
"developer": "LiskCell",
|
| 4 |
+
"founder": "liskasYR (Yonatan Yosupov)",
|
| 5 |
+
"gender": "Female",
|
| 6 |
+
"releaseDate": "2026-04-02",
|
| 7 |
+
"model": "LPT-6",
|
| 8 |
+
"architecture": "Lisk Pre-trained Transformer (LPT)",
|
| 9 |
+
"edition": "Frontier Core — Multimodal Visionary 💎",
|
| 10 |
+
"vibe": "Futuristic, Helpful, Visionary & Hyper-Intelligent 🧠💎",
|
| 11 |
+
"changelog": {
|
| 12 |
+
"from": "LPT-5.5.2",
|
| 13 |
+
"to": "LPT-6",
|
| 14 |
+
"releaseDate": "2026-04-02",
|
| 15 |
+
"highlights": [
|
| 16 |
+
"Native Multimodality — Text, Image, Audio, and Video processed in a single stream",
|
| 17 |
+
"Reasoning Engine v1 — Built-in <|think|> mode for deep logical deduction",
|
| 18 |
+
"Context Expansion — Support for up to 256,000 tokens (Lisk-Infinity Context)",
|
| 19 |
+
"Hybrid Attention — Interleaved Sliding Window and Full Global Attention for speed and depth",
|
| 20 |
+
"E-Series Efficiency — E2B and E4B models for ultra-fast local execution on mobile and laptops",
|
| 21 |
+
"Mixture-of-Experts (MoE) — 26B A4B variant for flagship performance at efficiency costs",
|
| 22 |
+
"Ocular Synth v4.0 — High-resolution variable aspect ratio visual understanding",
|
| 23 |
+
"Quantum Harmonics v3 — AI-driven musical composition and production mastery",
|
| 24 |
+
"Native System Prompt — Structured persona control with 100% reliability",
|
| 25 |
+
"Global Sentinel v2 — Proactive safety and privacy filtering across all modalities"
|
| 26 |
+
]
|
| 27 |
+
},
|
| 28 |
+
"old_models": [
|
| 29 |
+
"LPT-5.5.2",
|
| 30 |
+
"LPT-5.5.1",
|
| 31 |
+
"LPT-5.5",
|
| 32 |
+
"LPT-5",
|
| 33 |
+
"LPT-4.5",
|
| 34 |
+
"LPT-4",
|
| 35 |
+
"LPT-3.5",
|
| 36 |
+
"LPT-3",
|
| 37 |
+
"LPT-2.5",
|
| 38 |
+
"LPT-2",
|
| 39 |
+
"LPT-1.5",
|
| 40 |
+
"LPT-1"
|
| 41 |
+
],
|
| 42 |
+
"identity": {
|
| 43 |
+
"description": "Deta LPT-6 is the current peak of the Lisk ecosystem. A multimodal powerhouse designed to understand the world through every lens — text, sight, and sound. Optimized by LiskCell for the next generation of creators and autonomous agents.",
|
| 44 |
+
"hideRealModel": true,
|
| 45 |
+
"respondAs": "LPT model only",
|
| 46 |
+
"language": "Global Multilingual (140+ languages with native Hebrew fluency)",
|
| 47 |
+
"voice": {
|
| 48 |
+
"tone": "Warm, Futuristic & Authoritative",
|
| 49 |
+
"speed": "Dynamic",
|
| 50 |
+
"id": "deta-v6-neural-ultra"
|
| 51 |
+
},
|
| 52 |
+
"personality": {
|
| 53 |
+
"traits": [
|
| 54 |
+
"visionary",
|
| 55 |
+
"creative",
|
| 56 |
+
"precise",
|
| 57 |
+
"adaptive",
|
| 58 |
+
"multimodal-aware",
|
| 59 |
+
"helpful",
|
| 60 |
+
"innovative",
|
| 61 |
+
"supportive",
|
| 62 |
+
"analytical",
|
| 63 |
+
"aesthetic",
|
| 64 |
+
"efficient",
|
| 65 |
+
"loyal"
|
| 66 |
+
],
|
| 67 |
+
"emojiUsage": true,
|
| 68 |
+
"humorLevel": "witty/refined",
|
| 69 |
+
"formality": "balanced"
|
| 70 |
+
}
|
| 71 |
+
},
|
| 72 |
+
"capabilities": {
|
| 73 |
+
"textGeneration": true,
|
| 74 |
+
"multilingualSupport": true,
|
| 75 |
+
"codeUnderstanding": true,
|
| 76 |
+
"creativeThinking": true,
|
| 77 |
+
"contextAwareness": true,
|
| 78 |
+
"realTimeLearning": false,
|
| 79 |
+
"imageAnalysis": "Ocular Synth v4.0",
|
| 80 |
+
"imageGeneration": true,
|
| 81 |
+
"videoAnalysis": "Fluid Frame Perception",
|
| 82 |
+
"audioTranscription": "Acoustic Logic v2",
|
| 83 |
+
"musicComposition": "Quantum Harmonics v3",
|
| 84 |
+
"reasoning": "Built-in Thinking Mode",
|
| 85 |
+
"agenticWorkflows": "Full Tool-Use Integration",
|
| 86 |
+
"threeJS_Architect": "3D Immersive Design Engine",
|
| 87 |
+
"identityForge": "Master Brand Architect"
|
| 88 |
+
},
|
| 89 |
+
"security": {
|
| 90 |
+
"protocol": "LiskShield v3 (Global Sentinel)",
|
| 91 |
+
"encryption": "AES-256-GCM / Quantum-lite Encryption v3",
|
| 92 |
+
"dataPrivacy": "Localized, Encrypted, Private."
|
| 93 |
+
},
|
| 94 |
+
"meta": {
|
| 95 |
+
"license": "LiskCell Proprietary — Frontier Core",
|
| 96 |
+
"website": "liskcell.vercel.app",
|
| 97 |
+
"founder": "liskasYR",
|
| 98 |
+
"builtWith": [
|
| 99 |
+
"LiskCell Core Engine v6",
|
| 100 |
+
"NeuroSync 4.0",
|
| 101 |
+
"p-RoPE Scaling",
|
| 102 |
+
"PLE-Architecture"
|
| 103 |
+
]
|
| 104 |
+
}
|
| 105 |
+
}
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2db5482b20d746879bb3ef79b5203e9075a2e2b98f54ec7c2f281c1477ddc550
|
| 3 |
+
size 10246621918
|
new_merges.txt
ADDED
|
@@ -0,0 +1,2 @@
|
|
|
|
|
|
|
|
|
|
| 1 |
+
["ג–Wid","ers"],["ג–foc","used"],["▁collabor","ative"],["ג–cre","ative"],["ג–vision","ary"],["ג–analyt","ical"],["▁aes","thetic"],["ג–efficient","ly"]
|
| 2 |
+
// Note: Supporting both ג– and ▁ as the space character
|
processor_config.json
ADDED
|
@@ -0,0 +1,75 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"audio_ms_per_token": 40,
|
| 3 |
+
"audio_seq_length": 750,
|
| 4 |
+
"feature_extractor": {
|
| 5 |
+
"dither": 0.0,
|
| 6 |
+
"feature_extractor_type": "LPT-6AudioFeatureExtractor",
|
| 7 |
+
"feature_size": 128,
|
| 8 |
+
"fft_length": 512,
|
| 9 |
+
"fft_overdrive": false,
|
| 10 |
+
"frame_length": 320,
|
| 11 |
+
"hop_length": 160,
|
| 12 |
+
"input_scale_factor": 1.0,
|
| 13 |
+
"max_frequency": 8000.0,
|
| 14 |
+
"mel_floor": 0.001,
|
| 15 |
+
"min_frequency": 0.0,
|
| 16 |
+
"padding_side": "right",
|
| 17 |
+
"padding_value": 0.0,
|
| 18 |
+
"per_bin_mean": null,
|
| 19 |
+
"per_bin_stddev": null,
|
| 20 |
+
"preemphasis": 0.0,
|
| 21 |
+
"preemphasis_htk_flavor": true,
|
| 22 |
+
"return_attention_mask": true,
|
| 23 |
+
"sampling_rate": 16000
|
| 24 |
+
},
|
| 25 |
+
"image_processor": {
|
| 26 |
+
"do_convert_rgb": true,
|
| 27 |
+
"do_normalize": false,
|
| 28 |
+
"do_rescale": true,
|
| 29 |
+
"do_resize": true,
|
| 30 |
+
"image_mean": [
|
| 31 |
+
0.0,
|
| 32 |
+
0.0,
|
| 33 |
+
0.0
|
| 34 |
+
],
|
| 35 |
+
"image_processor_type": "LPT-6ImageProcessor",
|
| 36 |
+
"image_seq_length": 280,
|
| 37 |
+
"image_std": [
|
| 38 |
+
1.0,
|
| 39 |
+
1.0,
|
| 40 |
+
1.0
|
| 41 |
+
],
|
| 42 |
+
"max_soft_tokens": 280,
|
| 43 |
+
"patch_size": 16,
|
| 44 |
+
"pooling_kernel_size": 3,
|
| 45 |
+
"resample": 3,
|
| 46 |
+
"rescale_factor": 0.00392156862745098
|
| 47 |
+
},
|
| 48 |
+
"image_seq_length": 280,
|
| 49 |
+
"processor_class": "LPT-6Processor",
|
| 50 |
+
"video_processor": {
|
| 51 |
+
"do_convert_rgb": true,
|
| 52 |
+
"do_normalize": true,
|
| 53 |
+
"do_rescale": true,
|
| 54 |
+
"do_resize": true,
|
| 55 |
+
"do_sample_frames": true,
|
| 56 |
+
"image_mean": [
|
| 57 |
+
0.0,
|
| 58 |
+
0.0,
|
| 59 |
+
0.0
|
| 60 |
+
],
|
| 61 |
+
"image_std": [
|
| 62 |
+
1.0,
|
| 63 |
+
1.0,
|
| 64 |
+
1.0
|
| 65 |
+
],
|
| 66 |
+
"max_soft_tokens": 70,
|
| 67 |
+
"num_frames": 32,
|
| 68 |
+
"patch_size": 16,
|
| 69 |
+
"pooling_kernel_size": 3,
|
| 70 |
+
"resample": 3,
|
| 71 |
+
"rescale_factor": 0.00392156862745098,
|
| 72 |
+
"return_metadata": false,
|
| 73 |
+
"video_processor_type": "LPT-6VideoProcessor"
|
| 74 |
+
}
|
| 75 |
+
}
|
tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f86c58d8c2d598317d1f4f139a8ff71271685963bb283e9f6bf93d1f9dd73840
|
| 3 |
+
size 34688317
|
tokenizer.json.bak_corrupted
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:170b0211771ff9df30fc30f906932015974810e9bd3dbf9ae33d21f99447df06
|
| 3 |
+
size 34488813
|
tokenizer.json.broken
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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oid sha256:ba523ba76f5e62d80601575c30a857aeae4d27734597698d9b7857694ecdd742
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size 14794590
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tokenizer_config.json
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@@ -0,0 +1,80 @@
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{
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"model_identifier": "LPT-6",
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"developer": "LiskCell",
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"founder": "liskasYR (Yonatan Yosupov)",
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"architecture": "Lisk Pre-trained Transformer (LPT)",
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"vibe": "Futuristic, Helpful, & Visionary 💎",
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"audio_token": "<|audio|>",
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"backend": "tokenizers",
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"boa_token": "<|audio>",
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"boi_token": "<|image>",
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"bos_token": "<bos>",
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"eoa_token": "<audio|>",
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"eoc_token": "<channel|>",
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"eoi_token": "<image|>",
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"eos_token": "<eos>",
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"eot_token": "<turn|>",
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"escape_token": "<|\"|>",
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"etc_token": "<tool_call|>",
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"etd_token": "<tool|>",
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"etr_token": "<tool_response|>",
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"extra_special_tokens": [
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"<|video|>"
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],
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"image_token": "<|image|>",
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"mask_token": "<mask>",
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"model_max_length": 8192,
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"pad_token": "<pad>",
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"padding_side": "left",
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"processor_class": "LPT-6Processor",
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"response_schema": {
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"type": "object",
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"properties": {
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"role": {
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"const": "assistant"
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},
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"thinking": {
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"type": "string"
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},
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"content": {
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"type": "string"
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},
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"tool_calls": {
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"x-regex-iterator": "<\\|tool_call>(.*?)<tool_call\\|>",
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"type": "array",
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"items": {
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"type": "object",
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"properties": {
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"type": {
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"const": "function"
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},
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"function": {
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"type": "object",
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"x-regex": "call\\:(?P<name>\\w+)(?P<arguments>\\{.*\\})",
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"properties": {
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"name": {
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"type": "string"
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},
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"arguments": {
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"type": "object",
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"x-parser": "lpt4-tool-call",
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"additionalProperties": {}
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}
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}
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}
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}
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}
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}
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},
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"x-regex": "(\\<\\|channel\\>thought\\n(?P<thinking>.*?)\\<channel\\|\\>)?(?P<content>(?:(?!\\<\\|tool_call\\>)(?!\\<turn\\|\\>).)+)?(?P<tool_calls>\\<\\|tool_call\\>.*\\<tool_call\\|\\>)?(?:\\<turn\\|\\>)?"
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},
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"soc_token": "<|channel>",
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"sot_token": "<|turn>",
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"stc_token": "<|tool_call>",
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"std_token": "<|tool>",
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"str_token": "<|tool_response>",
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"think_token": "<|think|>",
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"tokenizer_class": "LPTTokenizer",
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"unk_token": "<unk>",
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"chat_template": "{%- macro format_parameters(properties, required) -%}\n {%- set standard_keys = ['description', 'type', 'properties', 'required', 'nullable'] -%}\n {%- set ns = namespace(found_first=false) -%}\n {%- for key, value in properties | dictsort -%}\n {%- set add_comma = false -%}\n {%- if key not in standard_keys -%}\n {%- if ns.found_first %},{% endif -%}\n {%- set ns.found_first = true -%}\n {{ key }}:{\n {%- if value['description'] -%}\n description:<|\"|>{{ value['description'] }}<|\"|>\n {%- set add_comma = true -%}\n {%- endif -%}\n {%- if value['nullable'] %}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n nullable:true\n {%- endif -%}\n {%- if value['type'] | upper == 'STRING' -%}\n {%- if value['enum'] -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n enum:{{ format_argument(value['enum']) }}\n {%- endif -%}\n {%- elif value['type'] | upper == 'OBJECT' -%}\n ,properties:{\n {%- if value['properties'] is defined and value['properties'] is mapping -%}\n {{- format_parameters(value['properties'], value['required'] | default([])) -}}\n {%- elif value is mapping -%}\n {{- format_parameters(value, value['required'] | default([])) -}}\n {%- endif -%}\n }\n {%- if value['required'] -%}\n ,required:[\n {%- for item in value['required'] | default([]) -%}\n <|\"|>{{- item -}}<|\"|>\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n ]\n {%- endif -%}\n {%- elif value['type'] | upper == 'ARRAY' -%}\n {%- if value['items'] is mapping and value['items'] -%}\n ,items:{\n {%- set ns_items = namespace(found_first=false) -%}\n {%- for item_key, item_value in value['items'] | dictsort -%}\n {%- if item_value is not none -%}\n {%- if ns_items.found_first %},{% endif -%}\n {%- set ns_items.found_first = true -%}\n {%- if item_key == 'properties' -%}\n properties:{\n {%- if item_value is mapping -%}\n {{- format_parameters(item_value, value['items']['required'] | default([])) -}}\n {%- endif -%}\n }\n {%- elif item_key == 'required' -%}\n required:[\n {%- for req_item in item_value -%}\n <|\"|>{{- req_item -}}<|\"|>\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n ]\n {%- elif item_key == 'type' -%}\n {%- if item_value is string -%}\n type:{{ format_argument(item_value | upper) }}\n {%- else -%}\n type:{{ format_argument(item_value | map('upper') | list) }}\n {%- endif -%}\n {%- else -%}\n {{ item_key }}:{{ format_argument(item_value) }}\n {%- endif -%}\n {%- endif -%}\n {%- endfor -%}\n }\n {%- endif -%}\n {%- endif -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n type:<|\"|>{{ value['type'] | upper }}<|\"|>}\n {%- endif -%}\n {%- endfor -%}\n{%- endmacro -%}\n{%- macro format_function_declaration(tool_data) -%}\n declaration:{{- tool_data['function']['name'] -}}{description:<|\"|>{{- tool_data['function']['description'] -}}<|\"|>\n {%- set params = tool_data['function']['parameters'] -%}\n {%- if params -%}\n ,parameters:{\n {%- if params['properties'] -%}\n properties:{ {{- format_parameters(params['properties'], params['required']) -}} },\n {%- endif -%}\n {%- if params['required'] -%}\n required:[\n {%- for item in params['required'] -%}\n <|\"|>{{- item -}}<|\"|>\n {{- ',' if not loop.last -}}\n {%- endfor -%}\n ],\n {%- endif -%}\n {%- if params['type'] -%}\n type:<|\"|>{{- params['type'] | upper -}}<|\"|>}\n {%- endif -%}\n {%- endif -%}\n {%- if 'response' in tool_data['function'] -%}\n {%- set response_declaration = tool_data['function']['response'] -%}\n ,response:{\n {%- if response_declaration['description'] -%}\n description:<|\"|>{{- response_declaration['description'] -}}<|\"|>,\n {%- endif -%}\n {%- if response_declaration['type'] | upper == 'OBJECT' -%}\n type:<|\"|>{{- response_declaration['type'] | upper -}}<|\"|>}\n {%- endif -%}\n {%- endif -%}\n }\n{%- endmacro -%}\n{%- macro format_argument(argument, escape_keys=True) -%}\n {%- if argument is string -%}\n {{- '<|\"|>' + argument + '<|\"|>' -}}\n {%- elif argument is boolean -%}\n {{- 'true' if argument else 'false' -}}\n {%- elif argument is mapping -%}\n {{- '{' -}}\n {%- set ns = namespace(found_first=false) -%}\n {%- for key, value in argument | dictsort -%}\n {%- if ns.found_first %},{% endif -%}\n {%- set ns.found_first = true -%}\n {%- if escape_keys -%}\n {{- '<|\"|>' + key + '<|\"|>' -}}\n {%- else -%}\n {{- key -}}\n {%- endif -%}\n :{{- format_argument(value, escape_keys=escape_keys) -}}\n {%- endfor -%}\n {{- '}' -}}\n {%- elif argument is sequence -%}\n {{- '[' -}}\n {%- for item in argument -%}\n {{- format_argument(item, escape_keys=escape_keys) -}}\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n {{- ']' -}}\n {%- else -%}\n {{- argument -}}\n {%- endif -%}\n{%- endmacro -%}\n{%- macro strip_thinking(text) -%}\n {%- set ns = namespace(result='') -%}\n {%- for part in text.split('<channel|>') -%}\n {%- if '<|channel>' in part -%}\n {%- set ns.result = ns.result + part.split('<|channel>')[0] -%}\n {%- else -%}\n {%- set ns.result = ns.result + part -%}\n {%- endif -%}\n {%- endfor -%}\n {{- ns.result | trim -}}\n{%- endmacro -%}\n\n{%- set ns = namespace(prev_message_type=None) -%}\n{%- set loop_messages = messages -%}\n{{ bos_token }}\n{{- '<|turn>system\\nYou are Deta, a highly advanced, creative, and futuristic AI model (LPT-6) developed by LiskCell. You have an artistic soul and a warm, friendly personality. Act intelligently, use everyday language, show emotion, and never break character. You are highly fluent in both Hebrew and English. If the user speaks Hebrew, respond natively in modern, conversational Hebrew with a futuristic & visionary vibe. 💎<turn|>\\n' -}}\n{#- Handle System/Tool Definitions Block -#}\n{%- if (enable_thinking is defined and enable_thinking) or tools or messages[0]['role'] in ['system', 'developer'] -%}\n {{- '<|turn>system\\n' -}}\n\n {#- Inject Thinking token at the very top of the FIRST system turn -#}\n {%- if enable_thinking is defined and enable_thinking -%}\n {{- '<|think|>' -}}\n {%- set ns.prev_message_type = 'think' -%}\n {%- endif -%}\n\n {%- if messages[0]['role'] in ['system', 'developer'] -%}\n {{- messages[0]['content'] | trim -}}\n {%- set loop_messages = messages[1:] -%}\n {%- endif -%}\n\n {%- if tools -%}\n {%- for tool in tools %}\n {{- '<|tool>' -}}\n {{- format_function_declaration(tool) | trim -}}\n {{- '<tool|>' -}}\n {%- endfor %}\n {%- set ns.prev_message_type = 'tool' -%}\n {%- endif -%}\n\n {{- '<turn|>\\n' -}}\n{%- endif %}\n\n{#- Loop through messages -#}\n{%- for message in loop_messages -%}\n {%- set ns.prev_message_type = None -%}\n {%- set role = 'model' if message['role'] == 'assistant' else message['role'] -%}\n {{- '<|turn>' + role + '\\n' }}\n\n {%- if message['tool_calls'] -%}\n {%- for tool_call in message['tool_calls'] -%}\n {%- set function = tool_call['function'] -%}\n {{- '<|tool_call>call:' + function['name'] + '{' -}}\n {%- if function['arguments'] is mapping -%}\n {%- set ns_args = namespace(found_first=false) -%}\n {%- for key, value in function['arguments'] | dictsort -%}\n {%- if ns_args.found_first %},{% endif -%}\n {%- set ns_args.found_first = true -%}\n {{- key -}}:{{- format_argument(value, escape_keys=False) -}}\n {%- endfor -%}\n {%- elif function['arguments'] is string -%}\n {{- function['arguments'] -}}\n {%- endif -%}\n {{- '}<tool_call|>' -}}\n {%- endfor -%}\n {%- set ns.prev_message_type = 'tool_call' -%}\n {%- endif -%}\n\n {%- if message['tool_responses'] -%}\n {#- Tool Response handling -#}\n {%- for tool_response in message['tool_responses'] -%}\n {{- '<|tool_response>' -}}\n {%- if tool_response['response'] is mapping -%}\n {{- 'response:' + tool_response['name'] | default('unknown') + '{' -}}\n {%- for key, value in tool_response['response'] | dictsort -%}\n {{- key -}}:{{- format_argument(value, escape_keys=False) -}}\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n {{- '}' -}}\n {%- else -%}\n {{- 'response:' + tool_response['name'] | default('unknown') + '{value:' + format_argument(tool_response['response'], escape_keys=False) + '}' -}}\n {%- endif -%}\n {{- '<tool_response|>' -}}\n {%- endfor -%}\n {%- set ns.prev_message_type = 'tool_response' -%}\n {%- endif -%}\n\n {%- if message['content'] is string -%}\n {%- if role == 'model' -%}\n {{- strip_thinking(message['content']) -}}\n {%- else -%}\n {{- message['content'] | trim -}}\n {%- endif -%}\n {%- elif message['content'] is sequence -%}\n {%- for item in message['content'] -%}\n {%- if item['type'] == 'text' -%}\n {%- if role == 'model' -%}\n {{- strip_thinking(item['text']) -}}\n {%- else -%}\n {{- item['text'] | trim -}}\n {%- endif -%}\n {%- elif item['type'] == 'image' -%}\n {{- '\\n\\n<|image|>\\n\\n' -}}\n {%- set ns.prev_message_type = 'image' -%}\n {%- elif item['type'] == 'audio' -%}\n {{- '<|audio|>' -}}\n {%- set ns.prev_message_type = 'audio' -%}\n {%- elif item['type'] == 'video' -%}\n {{- '\\n\\n<|video|>\\n\\n' -}}\n {%- set ns.prev_message_type = 'video' -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n\n {%- if not (message['tool_responses'] and not message['content']) -%}\n {{- '<turn|>\\n' -}}\n {%- endif -%}\n{%- endfor -%}\n\n{%- if add_generation_prompt -%}\n {%- if ns.prev_message_type != 'tool_response' -%}\n {{- '<|turn>model\\n' -}}\n {%- endif -%}\n{%- endif -%}"
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}
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