Instructions to use mecoffey/NPC_brain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries
PEFT
How to use mecoffey/NPC_brain with PEFT:
```
Task type is invalid.
```

How to use mecoffey/NPC_brain with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="mecoffey/NPC_brain")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("mecoffey/NPC_brain")
model = AutoModelForCausalLM.from_pretrained("mecoffey/NPC_brain", 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 mecoffey/NPC_brain with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mecoffey/NPC_brain"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mecoffey/NPC_brain",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/mecoffey/NPC_brain

SGLang

How to use mecoffey/NPC_brain 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 "mecoffey/NPC_brain" \
    --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": "mecoffey/NPC_brain",
		"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 "mecoffey/NPC_brain" \
        --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": "mecoffey/NPC_brain",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use mecoffey/NPC_brain with Docker Model Runner:
```
docker model run hf.co/mecoffey/NPC_brain
```

mecoffey commited on Jun 15

Commit

a3f8e5f

1 Parent(s): b1882c8

finalized param count

Browse files

Files changed (2) hide show

README.md +6 -20
adapter_config.json +0 -48

README.md CHANGED Viewed

@@ -19,18 +19,11 @@ I have specifically trained it to be the "Brain" of my app for the Build Small H
 - **Developed by:** mecoffey
-- **Model type:**
 - **Language:** English
 - **License:** apache-2.0
 - **Finetuned from model:** https://huggingface.co/openbmb/MiniCPM5-1B
-### Model Sources
-<!-- Provide the basic links for the model. -->
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
@@ -38,17 +31,10 @@ I have specifically trained it to be the "Brain" of my app for the Build Small H
 This model was trained with the following workflow in mind:
-- User prompt + system prompt = physical description of a fantasy character.
-- User prompt + generated description + new system prompt = a timeline backstory for the character to get to know them.
-My exact system prompts and model call are:
-'''
-ADD CODE HERE
-'''
-## How to Get Started with the Model
 ## Training Details
@@ -60,7 +46,7 @@ https://huggingface.co/datasets/mecoffey/npc_dataset
 ### Compute Infrastructure
-Trained with Modal GPU's
 ## Citation

 - **Developed by:** mecoffey
+- **Model type:** Causal Language Model
 - **Language:** English
 - **License:** apache-2.0
 - **Finetuned from model:** https://huggingface.co/openbmb/MiniCPM5-1B
+- **Total Parameters after fine-tune** 1,080,632,832
 This model was trained with the following workflow in mind:
+- User prompt = physical description of a fantasy character.
+- User prompt + generated description = a timeline backstory for the character to get to know them.
+The user prompt is designed to be short and simple. "something random", "a farmer" "a Half-Orc barkeep with a noticeable scar"
 ## Training Details
 ### Compute Infrastructure
+Trained with Modal GPUs
 ## Citation

adapter_config.json DELETED Viewed

@@ -1,48 +0,0 @@
-{
-  "alora_invocation_tokens": null,
-  "alpha_pattern": {},
-  "arrow_config": null,
-  "auto_mapping": null,
-  "base_model_name_or_path": "openbmb/MiniCPM5-1B",
-  "bias": "none",
-  "corda_config": null,
-  "ensure_weight_tying": false,
-  "eva_config": null,
-  "exclude_modules": null,
-  "fan_in_fan_out": false,
-  "inference_mode": true,
-  "init_lora_weights": true,
-  "layer_replication": null,
-  "layers_pattern": null,
-  "layers_to_transform": null,
-  "loftq_config": {},
-  "lora_alpha": 32,
-  "lora_bias": false,
-  "lora_dropout": 0.05,
-  "lora_ga_config": null,
-  "megatron_config": null,
-  "megatron_core": "megatron.core",
-  "modules_to_save": null,
-  "peft_type": "LORA",
-  "peft_version": "0.19.1",
-  "qalora_group_size": 16,
-  "r": 16,
-  "rank_pattern": {},
-  "revision": null,
-  "target_modules": [
-    "up_proj",
-    "q_proj",
-    "down_proj",
-    "v_proj",
-    "k_proj",
-    "gate_proj",
-    "o_proj"
-  ],
-  "target_parameters": null,
-  "task_type": "CAUSAL_LM",
-  "trainable_token_indices": null,
-  "use_bdlora": null,
-  "use_dora": false,
-  "use_qalora": false,
-  "use_rslora": false
-}