Quant for 6.5

README.md

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

added_tokens.json

@@ -0,0 +1,13 @@
+{
+  "<|assistant|>": 32001,
+  "<|endoftext|>": 32000,
+  "<|end|>": 32007,
+  "<|placeholder1|>": 32002,
+  "<|placeholder2|>": 32003,
+  "<|placeholder3|>": 32004,
+  "<|placeholder4|>": 32005,
+  "<|placeholder5|>": 32008,
+  "<|placeholder6|>": 32009,
+  "<|system|>": 32006,
+  "<|user|>": 32010
+}

config.json

@@ -0,0 +1,46 @@
+{
+    "_name_or_path": "microsoft/Phi-3-mini-4k-instruct",
+    "architectures": [
+        "Phi3ForCausalLM"
+    ],
+    "attention_dropout": 0.0,
+    "auto_map": {
+        "AutoConfig": "microsoft/Phi-3-mini-4k-instruct--configuration_phi3.Phi3Config",
+        "AutoModelForCausalLM": "microsoft/Phi-3-mini-4k-instruct--modeling_phi3.Phi3ForCausalLM"
+    },
+    "bos_token_id": 1,
+    "embd_pdrop": 0.0,
+    "eos_token_id": 32000,
+    "hidden_act": "silu",
+    "hidden_size": 3072,
+    "initializer_range": 0.02,
+    "intermediate_size": 8192,
+    "max_position_embeddings": 4096,
+    "model_type": "phi3",
+    "num_attention_heads": 32,
+    "num_hidden_layers": 32,
+    "num_key_value_heads": 32,
+    "original_max_position_embeddings": 4096,
+    "pad_token_id": 32000,
+    "resid_pdrop": 0.0,
+    "rms_norm_eps": 1e-05,
+    "rope_scaling": null,
+    "rope_theta": 10000.0,
+    "sliding_window": 2047,
+    "tie_word_embeddings": false,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.38.1",
+    "use_cache": true,
+    "vocab_size": 32064,
+    "quantization_config": {
+        "quant_method": "exl2",
+        "version": "0.0.20",
+        "bits": 6.5,
+        "head_bits": 8,
+        "calibration": {
+            "rows": 100,
+            "length": 2048,
+            "dataset": "(default)"
+        }
+    }
+}

generation_config.json

@@ -0,0 +1,11 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": [
+    32000,
+    32001,
+    32007
+  ],
+  "pad_token_id": 32000,
+  "transformers_version": "4.38.1"
+}

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