Instructions to use kashif/Qwen3-0.6B-h128-l4-a16-ctx256-pred64-vocab4096-MeanScaleUniform-lr1.0e-05-bs16-steps1000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use kashif/Qwen3-0.6B-h128-l4-a16-ctx256-pred64-vocab4096-MeanScaleUniform-lr1.0e-05-bs16-steps1000 with Transformers:

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

pipe = pipeline("text-generation", model="kashif/Qwen3-0.6B-h128-l4-a16-ctx256-pred64-vocab4096-MeanScaleUniform-lr1.0e-05-bs16-steps1000")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("kashif/Qwen3-0.6B-h128-l4-a16-ctx256-pred64-vocab4096-MeanScaleUniform-lr1.0e-05-bs16-steps1000")
model = AutoModelForCausalLM.from_pretrained("kashif/Qwen3-0.6B-h128-l4-a16-ctx256-pred64-vocab4096-MeanScaleUniform-lr1.0e-05-bs16-steps1000")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use kashif/Qwen3-0.6B-h128-l4-a16-ctx256-pred64-vocab4096-MeanScaleUniform-lr1.0e-05-bs16-steps1000 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "kashif/Qwen3-0.6B-h128-l4-a16-ctx256-pred64-vocab4096-MeanScaleUniform-lr1.0e-05-bs16-steps1000"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "kashif/Qwen3-0.6B-h128-l4-a16-ctx256-pred64-vocab4096-MeanScaleUniform-lr1.0e-05-bs16-steps1000",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/kashif/Qwen3-0.6B-h128-l4-a16-ctx256-pred64-vocab4096-MeanScaleUniform-lr1.0e-05-bs16-steps1000

SGLang

How to use kashif/Qwen3-0.6B-h128-l4-a16-ctx256-pred64-vocab4096-MeanScaleUniform-lr1.0e-05-bs16-steps1000 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 "kashif/Qwen3-0.6B-h128-l4-a16-ctx256-pred64-vocab4096-MeanScaleUniform-lr1.0e-05-bs16-steps1000" \
    --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": "kashif/Qwen3-0.6B-h128-l4-a16-ctx256-pred64-vocab4096-MeanScaleUniform-lr1.0e-05-bs16-steps1000",
		"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 "kashif/Qwen3-0.6B-h128-l4-a16-ctx256-pred64-vocab4096-MeanScaleUniform-lr1.0e-05-bs16-steps1000" \
        --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": "kashif/Qwen3-0.6B-h128-l4-a16-ctx256-pred64-vocab4096-MeanScaleUniform-lr1.0e-05-bs16-steps1000",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use kashif/Qwen3-0.6B-h128-l4-a16-ctx256-pred64-vocab4096-MeanScaleUniform-lr1.0e-05-bs16-steps1000 with Docker Model Runner:
```
docker model run hf.co/kashif/Qwen3-0.6B-h128-l4-a16-ctx256-pred64-vocab4096-MeanScaleUniform-lr1.0e-05-bs16-steps1000
```

kashif HF Staff commited on Jun 26, 2025

Commit

88abf98

verified ·

1 Parent(s): 0ff26b7

End of training

Browse files

Files changed (5) hide show

README.md +56 -0
config.json +37 -0
generation_config.json +7 -0
model.safetensors +3 -0
training_args.bin +3 -0

README.md ADDED Viewed

	@@ -0,0 +1,56 @@

+---
+library_name: transformers
+license: apache-2.0
+base_model: Qwen/Qwen3-0.6B
+tags:
+- generated_from_trainer
+model-index:
+- name: Qwen3-0.6B-h128-l4-a16-ctx256-pred64-vocab4096-MeanScaleUniform-lr1.0e-05-bs16-steps1000
+  results: []
+---
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+# Qwen3-0.6B-h128-l4-a16-ctx256-pred64-vocab4096-MeanScaleUniform-lr1.0e-05-bs16-steps1000
+This model is a fine-tuned version of [Qwen/Qwen3-0.6B](https://huggingface.co/Qwen/Qwen3-0.6B) on an unknown dataset.
+## Model description
+More information needed
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+More information needed
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 4
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.03
+- training_steps: 10000
+### Training results
+### Framework versions
+- Transformers 4.52.4
+- Pytorch 2.6.0+cu124
+- Datasets 3.6.0
+- Tokenizers 0.21.1

config.json ADDED Viewed

	@@ -0,0 +1,37 @@

+{
+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "binning_power": 2.0,
+  "bos_token_id": 2,
+  "context_length": 256,
+  "eos_token_id": 2,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 128,
+  "initializer_range": 0.02,
+  "intermediate_size": 256,
+  "max_position_embeddings": 40960,
+  "max_window_layers": 28,
+  "model_type": "qwen3",
+  "n_special_tokens": 2,
+  "num_attention_heads": 16,
+  "num_hidden_layers": 4,
+  "num_key_value_heads": 8,
+  "pad_token_id": 0,
+  "prediction_length": 64,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000,
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "tokenizer_class": "MeanScaleUniformBins",
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.52.4",
+  "use_cache": true,
+  "use_eos_token": false,
+  "use_sliding_window": false,
+  "vocab_size": 4096
+}

generation_config.json ADDED Viewed

	@@ -0,0 +1,7 @@

+{
+  "_from_model_config": true,
+  "bos_token_id": 2,
+  "eos_token_id": 2,
+  "pad_token_id": 0,
+  "transformers_version": "4.52.4"
+}

model.safetensors ADDED Viewed

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

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+size 8135768

training_args.bin ADDED Viewed

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