bartowski commited on
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Quant for 8.0

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README.md CHANGED
@@ -2,69 +2,139 @@
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  license: mit
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  language:
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  - en
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- quantized_by: bartowski
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- pipeline_tag: text-generation
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  ---
 
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- ## Exllama v2 Quantizations of NPC-LLM-3_8B
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- Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.20">turboderp's ExLlamaV2 v0.0.20</a> for quantization.
 
 
 
 
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- <b>The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)</b>
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- Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
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- Conversion was done using the default calibration dataset.
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- Default arguments used except when the bits per weight is above 6.0, at that point the lm_head layer is quantized at 8 bits per weight instead of the default 6.
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- Original model: https://huggingface.co/Gigax/NPC-LLM-3_8B
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- <a href="https://huggingface.co/bartowski/NPC-LLM-3_8B-exl2/tree/8_0">8.0 bits per weight</a>
 
 
 
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- <a href="https://huggingface.co/bartowski/NPC-LLM-3_8B-exl2/tree/6_5">6.5 bits per weight</a>
 
 
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- <a href="https://huggingface.co/bartowski/NPC-LLM-3_8B-exl2/tree/5_0">5.0 bits per weight</a>
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-
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- <a href="https://huggingface.co/bartowski/NPC-LLM-3_8B-exl2/tree/4_25">4.25 bits per weight</a>
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-
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- <a href="https://huggingface.co/bartowski/NPC-LLM-3_8B-exl2/tree/3_5">3.5 bits per weight</a>
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-
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-
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- ## Download instructions
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-
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- With git:
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-
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- ```shell
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- git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/NPC-LLM-3_8B-exl2
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  ```
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- With huggingface hub (credit to TheBloke for instructions):
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-
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- ```shell
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- pip3 install huggingface-hub
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
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- To download the `main` (only useful if you only care about measurement.json) branch to a folder called `NPC-LLM-3_8B-exl2`:
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-
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- ```shell
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- mkdir NPC-LLM-3_8B-exl2
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- huggingface-cli download bartowski/NPC-LLM-3_8B-exl2 --local-dir NPC-LLM-3_8B-exl2 --local-dir-use-symlinks False
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
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- To download from a different branch, add the `--revision` parameter:
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- Linux:
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- ```shell
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- mkdir NPC-LLM-3_8B-exl2-6_5
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- huggingface-cli download bartowski/NPC-LLM-3_8B-exl2 --revision 6_5 --local-dir NPC-LLM-3_8B-exl2-6_5 --local-dir-use-symlinks False
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- ```
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- Windows (which apparently doesn't like _ in folders sometimes?):
 
 
 
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- ```shell
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- mkdir NPC-LLM-3_8B-exl2-6.5
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- huggingface-cli download bartowski/NPC-LLM-3_8B-exl2 --revision 6_5 --local-dir NPC-LLM-3_8B-exl2-6.5 --local-dir-use-symlinks False
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- ```
 
 
 
 
 
 
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  license: mit
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  language:
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  - en
 
 
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  ---
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+ # NPC Model
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+ This repo contains the domain-specific NPC model we've fined-tuned from **Phi-3**, using LoRA.
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+ This model parses a text description of a game scene, and outputs commands like:
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+ * `say <player1> "Hello Adventurer, care to join me on a quest?`
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+ * `greet <player1>`
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+ * `attack <player1>`
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+ * Any other `<action> <param>` you add to the prompt! (We call these "skills"!)
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+ ⚠️ This model has been trained to **overfit** on our input prompt format. Follow it closely to reach optimal performance ⚠️
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+ ## Usage
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+ **Make your life easier, use our [Python client library](https://github.com/GigaxGames/gigax)**
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+ * Instantiating the model using outlines:
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+ ```py
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+ from outlines import models
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+ from gigax.step import NPCStepper
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+ # Download model from the Hub
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+ model_name = "Gigax/NPC-LLM-7B"
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+ llm = AutoModelForCausalLM.from_pretrained(model_name)
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+ tokenizer = AutoTokenizer.from_pretrained(model_name)
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+ # Our stepper takes in a Outlines model to enable guided generation
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+ # This forces the model to follow our output format
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+ model = models.Transformers(llm, tokenizer)
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+ # Instantiate a stepper: handles prompting + output parsing
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+ stepper = NPCStepper(model=model)
 
 
 
 
 
 
 
 
 
 
 
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  ```
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+ * Calling the model on your game's data:
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+
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+ ```py
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+ from gigax.parse import CharacterAction
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+ from gigax.scene import (
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+ Character,
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+ Item,
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+ Location,
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+ ProtagonistCharacter,
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+ ProtagonistCharacter,
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+ Skill,
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+ ParameterType,
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+ )
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+ # Use sample data
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+ current_location = Location(name="Old Town", description="A quiet and peaceful town.")
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+ NPCs = [
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+ Character(
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+ name="John the Brave",
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+ description="A fearless warrior",
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+ current_location=current_location,
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+ )
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+ ]
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+ protagonist = ProtagonistCharacter(
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+ name="Aldren",
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+ description="Brave and curious",
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+ current_location=current_location,
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+ memories=["Saved the village", "Lost a friend"],
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+ quests=["Find the ancient artifact", "Defeat the evil warlock"],
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+ skills=[
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+ Skill(
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+ name="Attack",
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+ description="Deliver a powerful blow",
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+ parameter_types=[ParameterType.character],
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+ )
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+ ],
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+ psychological_profile="Determined and compassionate",
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+ )
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+ items = [Item(name="Sword", description="A sharp blade")]
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+ events = [
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+ CharacterAction(
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+ command="Say",
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+ protagonist=protagonist,
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+ parameters=[items[0], "What a fine sword!"],
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+ )
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+ ]
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+
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+ action = stepper.get_action(
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+ context=context,
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+ locations=locations,
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+ NPCs=NPCs,
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+ protagonist=protagonist,
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+ items=items,
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+ events=events,
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+ )
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  ```
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+ ## Input prompt
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+
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+ Here's a sample input prompt, showing you the format on which the model has been trained:
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+ ```txt
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+ - WORLD KNOWLEDGE: A vast open world full of mystery and adventure.
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+ - KNOWN LOCATIONS: Old Town
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+ - NPCS: John the Brave
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+ - CURRENT LOCATION: Old Town: A quiet and peaceful town.
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+ - CURRENT LOCATION ITEMS: Sword
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+ - LAST EVENTS:
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+ Aldren: Say Sword What a fine sword!
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+ - PROTAGONIST NAME: Aldren
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+ - PROTAGONIST PSYCHOLOGICAL PROFILE: Brave and curious
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+ - PROTAGONIST MEMORIES:
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+ Saved the village
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+ Lost a friend
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+ - PROTAGONIST PENDING QUESTS:
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+ Find the ancient artifact
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+ Defeat the evil warlock
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+ - PROTAGONIST ALLOWED ACTIONS:
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+ Attack <character> : Deliver a powerful blow
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+ Aldren:
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  ```
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+ ### 🤗 We are currently working hard on training on the latest SoTA models (Phi-3, LLama, etc.), and on better data ! 🤗
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+ ## Model info
 
 
 
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+ - **Developed by:** Gigax
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+ - **Language(s) (NLP):** English
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+ - **Finetuned from model [optional]:** [Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct)
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+ - **Contact:** Join our [Discord](https://discord.gg/xES2Z8X4J6) for info, help, and more!
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+ ## How to Cite
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+
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+ ```bibtex
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+ @misc{NPC-LLM-3_8B,
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+ url={[https://huggingface.co/Gigax/NPC-LLM-7B](https://huggingface.co/Gigax/NPC-LLM-3_8B)},
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+ title={NPC-LLM-3_8B},
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+ author={Gigax team}
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+ }
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+ ```
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