Instructions to use Azmainadeeb/gpt-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Azmainadeeb/gpt-sft with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Azmainadeeb/gpt-sft")
model = AutoModelForCausalLM.from_pretrained("Azmainadeeb/gpt-sft")
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 Azmainadeeb/gpt-sft with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/Azmainadeeb/gpt-sft

SGLang

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

Unsloth Studio new

How to use Azmainadeeb/gpt-sft with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Azmainadeeb/gpt-sft to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Azmainadeeb/gpt-sft to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Azmainadeeb/gpt-sft to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="Azmainadeeb/gpt-sft",
    max_seq_length=2048,
)

Docker Model Runner
How to use Azmainadeeb/gpt-sft with Docker Model Runner:
```
docker model run hf.co/Azmainadeeb/gpt-sft
```

Azmainadeeb commited on Feb 4

Commit

03e5862

verified ·

1 Parent(s): d5f23d2

(Trained with Unsloth)

Browse files

Files changed (2) hide show

config.json +82 -0
tokenizer_config.json +3 -2

config.json ADDED Viewed

	@@ -0,0 +1,82 @@

+{
+    "architectures": [
+        "GptOssForCausalLM"
+    ],
+    "attention_bias": true,
+    "attention_dropout": 0.0,
+    "bos_token_id": 199998,
+    "torch_dtype": "bfloat16",
+    "eos_token_id": 200002,
+    "experts_per_token": 4,
+    "head_dim": 64,
+    "hidden_act": "silu",
+    "hidden_size": 2880,
+    "initial_context_length": 4096,
+    "initializer_range": 0.02,
+    "intermediate_size": 2880,
+    "layer_types": [
+        "sliding_attention",
+        "full_attention",
+        "sliding_attention",
+        "full_attention",
+        "sliding_attention",
+        "full_attention",
+        "sliding_attention",
+        "full_attention",
+        "sliding_attention",
+        "full_attention",
+        "sliding_attention",
+        "full_attention",
+        "sliding_attention",
+        "full_attention",
+        "sliding_attention",
+        "full_attention",
+        "sliding_attention",
+        "full_attention",
+        "sliding_attention",
+        "full_attention",
+        "sliding_attention",
+        "full_attention",
+        "sliding_attention",
+        "full_attention",
+        "sliding_attention",
+        "full_attention",
+        "sliding_attention",
+        "full_attention",
+        "sliding_attention",
+        "full_attention",
+        "sliding_attention",
+        "full_attention",
+        "sliding_attention",
+        "full_attention",
+        "sliding_attention",
+        "full_attention"
+    ],
+    "max_position_embeddings": 131072,
+    "model_type": "gpt_oss",
+    "num_attention_heads": 64,
+    "num_experts_per_tok": 4,
+    "num_hidden_layers": 36,
+    "num_key_value_heads": 8,
+    "num_local_experts": 128,
+    "output_router_logits": false,
+    "pad_token_id": 200017,
+    "rms_norm_eps": 1e-05,
+    "rope_scaling": {
+        "beta_fast": 32.0,
+        "beta_slow": 1.0,
+        "factor": 32.0,
+        "original_max_position_embeddings": 4096,
+        "rope_type": "yarn",
+        "truncate": false
+    },
+    "rope_theta": 150000,
+    "router_aux_loss_coef": 0.9,
+    "sliding_window": 128,
+    "swiglu_limit": 7.0,
+    "tie_word_embeddings": false,
+    "unsloth_fixed": true,
+    "unsloth_version": "2026.1.4",
+    "use_cache": true,
+    "vocab_size": 201088
+}

tokenizer_config.json CHANGED Viewed

@@ -181,5 +181,6 @@
   "pad_token": "<|reserved_200017|>",
   "padding_side": "left",
   "tokenizer_class": "PreTrainedTokenizerFast",
-  "unk_token": null
-}

   "pad_token": "<|reserved_200017|>",
   "padding_side": "left",
   "tokenizer_class": "PreTrainedTokenizerFast",
+  "unk_token": null,
+  "chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}<|start|>system<|message|># Instructions\n\n{{ message['content'] }}<|end|>{% elif message['role'] == 'user' %}<|start|>user<|message|>{{ message['content'] }}<|end|>{% elif message['role'] == 'assistant' %}<|start|>assistant<|message|>{{ message['content'] }}<|return|>{% endif %}{% endfor %}"
+}