Instructions to use oddadmix/Nawah-Math-Reasoning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use oddadmix/Nawah-Math-Reasoning with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("oddadmix/Nawah-Math-Reasoning")
model = AutoModelForCausalLM.from_pretrained("oddadmix/Nawah-Math-Reasoning", 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 oddadmix/Nawah-Math-Reasoning with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/oddadmix/Nawah-Math-Reasoning

SGLang

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

Docker Model Runner
How to use oddadmix/Nawah-Math-Reasoning with Docker Model Runner:
```
docker model run hf.co/oddadmix/Nawah-Math-Reasoning
```

oddadmix commited on 6 days ago

Commit

594647f

verified ·

1 Parent(s): 141c48b

Nawah-Math-Reasoning: weights, tokenizer, eval + training metrics

Browse files

Files changed (9) hide show

chat_template.jinja +4 -0
config.json +32 -0
eval_reasoning.json +0 -0
generation_config.json +13 -0
model.safetensors +3 -0
tokenizer.json +0 -0
tokenizer_config.json +17 -0
train_metrics.json +0 -0
training_args.bin +3 -0

chat_template.jinja ADDED Viewed

	@@ -0,0 +1,4 @@

+{% for message in messages %}{{ '<|im_start|>' + message['role'] + '
+' + message['content'] + '<|im_end|>' + '
+' }}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
+' }}{% endif %}

config.json ADDED Viewed

	@@ -0,0 +1,32 @@

+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 0,
+  "dtype": "float32",
+  "eos_token_id": 2,
+  "head_dim": 64,
+  "hidden_act": "silu",
+  "hidden_size": 512,
+  "initializer_range": 0.02,
+  "intermediate_size": 1408,
+  "max_position_embeddings": 2048,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 8,
+  "num_hidden_layers": 12,
+  "num_key_value_heads": 4,
+  "pad_token_id": 1,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 10000,
+    "rope_type": "default"
+  },
+  "tie_word_embeddings": true,
+  "transformers_version": "5.15.0",
+  "use_cache": true,
+  "vocab_size": 32004
+}

eval_reasoning.json ADDED Viewed

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generation_config.json ADDED Viewed

	@@ -0,0 +1,13 @@

+{
+  "_from_model_config": true,
+  "bos_token_id": 0,
+  "eos_token_id": [
+    2,
+    32001
+  ],
+  "output_attentions": false,
+  "output_hidden_states": false,
+  "pad_token_id": 1,
+  "transformers_version": "5.15.0",
+  "use_cache": true
+}

model.safetensors ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:347087691344b62fb82f7b7357284d83a7311f6c61653ae141eb584b29f920c5
+size 207165328

tokenizer.json ADDED Viewed

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tokenizer_config.json ADDED Viewed

	@@ -0,0 +1,17 @@

+{
+  "backend": "tokenizers",
+  "bos_token": "<s>",
+  "eos_token": "</s>",
+  "extra_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<think>",
+    "</think>"
+  ],
+  "is_local": true,
+  "local_files_only": false,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<pad>",
+  "tokenizer_class": "TokenizersBackend",
+  "unk_token": "<unk>"
+}

train_metrics.json ADDED Viewed

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training_args.bin ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:b17e37a1335e3021858b9137cd1549107fd7215edee8139833f122d34eb1fa45
+size 5201