Instructions to use Ba2han/TR_SFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Ba2han/TR_SFT with Transformers:

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

pipe = pipeline("text-generation", model="Ba2han/TR_SFT")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Ba2han/TR_SFT")
model = AutoModelForCausalLM.from_pretrained("Ba2han/TR_SFT", 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 Ba2han/TR_SFT with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Ba2han/TR_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": "Ba2han/TR_SFT",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Ba2han/TR_SFT

SGLang

How to use Ba2han/TR_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 "Ba2han/TR_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": "Ba2han/TR_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 "Ba2han/TR_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": "Ba2han/TR_SFT",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio

How to use Ba2han/TR_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 Ba2han/TR_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 Ba2han/TR_SFT to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Ba2han/TR_SFT to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="Ba2han/TR_SFT",
    max_seq_length=2048,
)

Docker Model Runner
How to use Ba2han/TR_SFT with Docker Model Runner:
```
docker model run hf.co/Ba2han/TR_SFT
```

Ba2han commited on 23 days ago

Commit

51af747

verified ·

1 Parent(s): 074f45c

Training in progress, step 474

Browse files

Files changed (6) hide show

README.md +4 -5
config.json +1 -1
model.safetensors +1 -1
tokenizer.json +1 -6
tokenizer_config.json +2 -2
training_args.bin +2 -2

README.md CHANGED Viewed

@@ -1,18 +1,17 @@
 ---
-base_model: Ba2han/outputs
 library_name: transformers
 model_name: TR_SFT
 tags:
 - generated_from_trainer
 - trl
 - sft
-- unsloth
 licence: license
 ---
 # Model Card for TR_SFT
-This model is a fine-tuned version of [Ba2han/outputs](https://huggingface.co/Ba2han/outputs).
 It has been trained using [TRL](https://github.com/huggingface/trl).
 ## Quick start
@@ -28,7 +27,7 @@ print(output["generated_text"])
 ## Training procedure
-[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/batuhan409/huggingface/runs/a7ick3bl)
 This model was trained with SFT.
@@ -38,7 +37,7 @@ This model was trained with SFT.
 - TRL: 0.24.0
 - Transformers: 5.5.0
 - Pytorch: 2.10.0+cu128
-- Datasets: 4.3.0
 - Tokenizers: 0.22.2
 ## Citations

 ---
 library_name: transformers
 model_name: TR_SFT
 tags:
 - generated_from_trainer
+- unsloth
 - trl
 - sft
 licence: license
 ---
 # Model Card for TR_SFT
+This model is a fine-tuned version of [None](https://huggingface.co/None).
 It has been trained using [TRL](https://github.com/huggingface/trl).
 ## Quick start
 ## Training procedure
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/batuhan409/huggingface/runs/vlcy4szp)
 This model was trained with SFT.
 - TRL: 0.24.0
 - Transformers: 5.5.0
 - Pytorch: 2.10.0+cu128
+- Datasets: 4.6.0
 - Tokenizers: 0.22.2
 ## Citations

config.json CHANGED Viewed

@@ -58,7 +58,7 @@
   ],
   "max_position_embeddings": 16384,
   "max_window_layers": 42,
-  "model_name": "Ba2han/outputs",
   "model_type": "qwen3",
   "num_attention_heads": 12,
   "num_hidden_layers": 42,

   ],
   "max_position_embeddings": 16384,
   "max_window_layers": 42,
+  "model_name": "TR_CPT1/checkpoint-10000",
   "model_type": "qwen3",
   "num_attention_heads": 12,
   "num_hidden_layers": 42,

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tokenizer.json CHANGED Viewed

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 {
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-    "strategy": "LongestFirst",
-    "stride": 0
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   "added_tokens": [
     {

 {
   "version": "1.0",
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tokenizer_config.json CHANGED Viewed

@@ -3,10 +3,10 @@
   "bos_token": "<bos>",
   "clean_up_tokenization_spaces": false,
   "eos_token": "<eos>",
-  "is_local": false,
   "model_max_length": 1000000000000000019884624838656,
   "pad_token": "<pad>",
-  "padding_side": "left",
   "tokenizer_class": "TokenizersBackend",
   "unk_token": "<unk>",
   "added_tokens_decoder": {

   "bos_token": "<bos>",
   "clean_up_tokenization_spaces": false,
   "eos_token": "<eos>",
+  "is_local": true,
   "model_max_length": 1000000000000000019884624838656,
   "pad_token": "<pad>",
+  "padding_side": "right",
   "tokenizer_class": "TokenizersBackend",
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   "added_tokens_decoder": {

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