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Training in progress, epoch 1

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README.md ADDED
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+ ---
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+ base_model: HuggingFaceTB/SmolLM2-135M-Instruct
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+ library_name: transformers
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+ model_name: yolo-mode
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+ tags:
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+ - generated_from_trainer
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+ - trl
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+ - trackio:https://lewtun-mlintern-yolomode.hf.space?project=huggingface&runs=sft-smollm2-135m-capybara100&sidebar=collapsed
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+ - sft
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+ licence: license
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+ ---
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+
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+ # Model Card for yolo-mode
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+
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+ This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct).
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+ It has been trained using [TRL](https://github.com/huggingface/trl).
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+
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+ ## Quick start
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+
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+ ```python
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+ from transformers import pipeline
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+
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+ question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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+ generator = pipeline("text-generation", model="lewtun/yolo-mode", device="cuda")
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+ output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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+ print(output["generated_text"])
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+ ```
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+
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+ ## Training procedure
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+
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+
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+ [<img src="https://raw.githubusercontent.com/gradio-app/trackio/refs/heads/main/trackio/assets/badge.png" alt="Visualize in Trackio" title="Visualize in Trackio" width="150" height="24"/>](https://lewtun-mlintern-yolomode.hf.space?project=huggingface&runs=sft-smollm2-135m-capybara100&sidebar=collapsed)
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+
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+
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+ This model was trained with SFT.
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+
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+ ### Framework versions
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+
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+ - TRL: 1.3.0
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+ - Transformers: 5.7.0
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+ - Pytorch: 2.11.0
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+ - Datasets: 4.8.5
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+ - Tokenizers: 0.22.2
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+
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+ ## Citations
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+
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+
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+
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+ Cite TRL as:
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+
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+ ```bibtex
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+ @software{vonwerra2020trl,
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+ title = {{TRL: Transformers Reinforcement Learning}},
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+ author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
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+ license = {Apache-2.0},
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+ url = {https://github.com/huggingface/trl},
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+ year = {2020}
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+ }
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+ ```
chat_template.jinja ADDED
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+ {% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system
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+ You are a helpful AI assistant named SmolLM, trained by Hugging Face<|im_end|>
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+ ' }}{% endif %}{{'<|im_start|>' + message['role'] + '
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+ ' + message['content'] + '<|im_end|>' + '
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+ '}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
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+ ' }}{% endif %}
config.json ADDED
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+ {
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+ "architectures": [
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+ "LlamaForCausalLM"
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+ ],
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+ "attention_bias": false,
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 1,
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+ "dtype": "float32",
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+ "eos_token_id": 2,
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+ "head_dim": 64,
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+ "hidden_act": "silu",
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+ "hidden_size": 576,
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+ "initializer_range": 0.041666666666666664,
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+ "intermediate_size": 1536,
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+ "is_llama_config": true,
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+ "max_position_embeddings": 8192,
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+ "mlp_bias": false,
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+ "model_type": "llama",
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+ "num_attention_heads": 9,
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+ "num_hidden_layers": 30,
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+ "num_key_value_heads": 3,
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+ "pad_token_id": 2,
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+ "pretraining_tp": 1,
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+ "rms_norm_eps": 1e-05,
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+ "rope_interleaved": false,
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+ "rope_parameters": {
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+ "rope_theta": 100000,
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+ "rope_type": "default"
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+ },
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+ "tie_word_embeddings": true,
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+ "transformers.js_config": {
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+ "kv_cache_dtype": {
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+ "fp16": "float16",
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+ "q4f16": "float16"
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+ }
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+ },
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+ "transformers_version": "5.7.0",
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+ "use_cache": false,
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+ "vocab_size": 49152
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+ }
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+ {
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+ 2
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+ "pad_token_id": 2,
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+ "transformers_version": "5.7.0"
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+ }
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+ "tokenizer_class": "GPT2Tokenizer",
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+ "unk_token": "<|endoftext|>",
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+ "vocab_size": 49152
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+ }
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