Instructions to use Clemylia/Charlotte-AMITY with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Clemylia/Charlotte-AMITY with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Clemylia/Charlotte-AMITY")
model = AutoModelForCausalLM.from_pretrained("Clemylia/Charlotte-AMITY")
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

vLLM

How to use Clemylia/Charlotte-AMITY with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/Clemylia/Charlotte-AMITY

SGLang

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

Docker Model Runner
How to use Clemylia/Charlotte-AMITY with Docker Model Runner:
```
docker model run hf.co/Clemylia/Charlotte-AMITY
```

Clemylia commited on Nov 21, 2025

Commit

a087e81

verified ·

1 Parent(s): 3c18137

Update config.json

Browse files

Files changed (1) hide show

config.json +3 -3

config.json CHANGED Viewed

@@ -1,7 +1,7 @@
 {
   "activation_function": "gelu_new",
   "architectures": [
-    "CharlotteAmityForCausalLM"
   ],
   "attn_pdrop": 0.1,
   "bos_token_id": 50256,
@@ -10,7 +10,7 @@
   "eos_token_id": 50256,
   "initializer_range": 0.02,
   "layer_norm_epsilon": 1e-05,
-  "model_type": "charlotte",
   "n_embd": 512,
   "n_head": 8,
   "n_inner": null,
@@ -29,4 +29,4 @@
   "transformers_version": "4.57.1",
   "use_cache": true,
   "vocab_size": 50258
-}

 {
   "activation_function": "gelu_new",
   "architectures": [
+    "GPT2LMHeadModel"
   ],
   "attn_pdrop": 0.1,
   "bos_token_id": 50256,
   "eos_token_id": 50256,
   "initializer_range": 0.02,
   "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
   "n_embd": 512,
   "n_head": 8,
   "n_inner": null,
   "transformers_version": "4.57.1",
   "use_cache": true,
   "vocab_size": 50258
+}