Instructions to use Ba2han/experimental2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Ba2han/experimental2 with Transformers:

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

pipe = pipeline("text-generation", model="Ba2han/experimental2", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Ba2han/experimental2", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("Ba2han/experimental2", trust_remote_code=True)

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Ba2han/experimental2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Ba2han/experimental2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Ba2han/experimental2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Ba2han/experimental2

SGLang

How to use Ba2han/experimental2 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/experimental2" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Ba2han/experimental2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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/experimental2" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Ba2han/experimental2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Unsloth Studio new

How to use Ba2han/experimental2 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/experimental2 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/experimental2 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Ba2han/experimental2 to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="Ba2han/experimental2",
    max_seq_length=2048,
)

Docker Model Runner
How to use Ba2han/experimental2 with Docker Model Runner:
```
docker model run hf.co/Ba2han/experimental2
```

Ba2han commited on 17 days ago

Commit

c31ae10

1 Parent(s): d4bd2e0

Training in progress, step 975

Browse files

Files changed (3) hide show

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

README.md CHANGED Viewed

@@ -3,9 +3,9 @@ library_name: transformers
 model_name: experimental2
 tags:
 - generated_from_trainer
-- unsloth
 - trl
 - sft
 licence: license
 ---
@@ -27,7 +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/8fcww366)
 This model was trained with SFT.
@@ -35,7 +35,7 @@ This model was trained with SFT.
 ### Framework versions
 - TRL: 0.24.0
-- Transformers: 5.6.2
 - Pytorch: 2.10.0
 - Datasets: 4.3.0
 - Tokenizers: 0.22.2

 model_name: experimental2
 tags:
 - generated_from_trainer
 - trl
 - sft
+- unsloth
 licence: license
 ---
 ## 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/0blltk43)
 This model was trained with SFT.
 ### Framework versions
 - TRL: 0.24.0
+- Transformers: 5.7.0
 - Pytorch: 2.10.0
 - Datasets: 4.3.0
 - Tokenizers: 0.22.2

config.json CHANGED Viewed

@@ -14,7 +14,7 @@
   "hidden_act": "silu",
   "hidden_size": 1024,
   "initializer_range": 0.02,
-  "intermediate_size": 4096,
   "layer_types": [
     "full_attention",
     "full_attention",
@@ -63,7 +63,7 @@
   "max_window_layers": 42,
   "model_name": "test_checkpoint",
   "model_type": "qwen3",
-  "num_attention_heads": 12,
   "num_hidden_layers": 42,
   "num_key_value_heads": 4,
   "pad_token_id": 50034,
@@ -80,7 +80,7 @@
   "softcap_scale": 23.0,
   "softcap_shift": 5.0,
   "tie_word_embeddings": true,
-  "transformers_version": "5.6.2",
   "unsloth_version": "2026.4.8",
   "use_cache": false,
   "use_qk_norm_patch": true,

   "hidden_act": "silu",
   "hidden_size": 1024,
   "initializer_range": 0.02,
+  "intermediate_size": 2816,
   "layer_types": [
     "full_attention",
     "full_attention",
   "max_window_layers": 42,
   "model_name": "test_checkpoint",
   "model_type": "qwen3",
+  "num_attention_heads": 16,
   "num_hidden_layers": 42,
   "num_key_value_heads": 4,
   "pad_token_id": 50034,
   "softcap_scale": 23.0,
   "softcap_shift": 5.0,
   "tie_word_embeddings": true,
+  "transformers_version": "5.7.0",
   "unsloth_version": "2026.4.8",
   "use_cache": false,
   "use_qk_norm_patch": true,

generation_config.json CHANGED Viewed

@@ -8,6 +8,6 @@
   "output_attentions": false,
   "output_hidden_states": false,
   "pad_token_id": 50034,
-  "transformers_version": "5.6.2",
   "use_cache": false
 }

   "output_attentions": false,
   "output_hidden_states": false,
   "pad_token_id": 50034,
+  "transformers_version": "5.7.0",
   "use_cache": false
 }