Instructions to use waddie/mini-2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use waddie/mini-2.0 with Transformers:

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

pipe = pipeline("text-generation", model="waddie/mini-2.0")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("waddie/mini-2.0")
model = AutoModelForCausalLM.from_pretrained("waddie/mini-2.0")
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 waddie/mini-2.0 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "waddie/mini-2.0"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "waddie/mini-2.0",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/waddie/mini-2.0

SGLang

How to use waddie/mini-2.0 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 "waddie/mini-2.0" \
    --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": "waddie/mini-2.0",
		"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 "waddie/mini-2.0" \
        --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": "waddie/mini-2.0",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use waddie/mini-2.0 with Docker Model Runner:
```
docker model run hf.co/waddie/mini-2.0
```

waddie commited on 26 days ago

Commit

b2c30f2

verified ·

1 Parent(s): c8c9e17

Upload Qwen3_5ForCausalLM

Browse files

Files changed (3) hide show

README.md +3 -1
config.json +2 -2
generation_config.json +5 -1

README.md CHANGED Viewed

@@ -1,6 +1,8 @@
 ---
 library_name: transformers
-tags: []
 ---
 # Model Card for Model ID

 ---
 library_name: transformers
+tags:
+- trl
+- sft
 ---
 # Model Card for Model ID

config.json CHANGED Viewed

@@ -7,7 +7,7 @@
   "attn_output_gate": true,
   "bos_token_id": null,
   "dtype": "bfloat16",
-  "eos_token_id": 248044,
   "full_attention_interval": 4,
   "head_dim": 256,
   "hidden_act": "silu",
@@ -78,6 +78,6 @@
   },
   "tie_word_embeddings": false,
   "transformers_version": "5.6.2",
-  "use_cache": true,
   "vocab_size": 248320
 }

   "attn_output_gate": true,
   "bos_token_id": null,
   "dtype": "bfloat16",
+  "eos_token_id": 248046,
   "full_attention_interval": 4,
   "head_dim": 256,
   "hidden_act": "silu",
   },
   "tie_word_embeddings": false,
   "transformers_version": "5.6.2",
+  "use_cache": false,
   "vocab_size": 248320
 }

generation_config.json CHANGED Viewed

@@ -1,6 +1,10 @@
 {
   "_from_model_config": true,
-  "eos_token_id": 248044,
   "transformers_version": "5.6.2",
   "use_cache": true
 }

 {
   "_from_model_config": true,
+  "eos_token_id": [
+    248046,
+    248044
+  ],
+  "pad_token_id": 248055,
   "transformers_version": "5.6.2",
   "use_cache": true
 }