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Model: Shekswess/trlm-stage-1-sft-final-2 Source: Original Platform
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README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: HuggingFaceTB/SmolLM2-135M-Instruct
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tags:
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- trl
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- sft
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- generated_from_trainer
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model-index:
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- name: trlm-stage-1-sft-final-2
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results: []
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---
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# 🧠 trlm-stage-1-sft-final-2
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`trlm-stage-1-sft-final-2` is the **Stage 1** post-training model for the **Tiny Reasoning Language Model (trlm)** project.
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This stage focuses on **everyday conversations** and **general instruction following**, fine-tuned on a curated dataset of **58,000 entries**.
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---
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## 📖 Model Description
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- **Base Model**: [HuggingFaceTB/SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct)
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- **Type**: Causal Language Model (decoder-only transformer)
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- **Stage**: Post-training **Stage 1 (SFT)**
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- **Objective**: Build a solid foundation in **instruction-following** and **dialogue coherence** before advancing to reasoning-specific training.
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This stage teaches the model to **follow instructions, rewrite, summarize, and hold conversations** without reasoning tokens.
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---
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## 🎯 Intended Uses & Limitations
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### Intended Uses
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- Everyday conversation assistants
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- Instruction-following tasks (summarization, rewriting, simple dialogue)
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- Precursor foundation for reasoning post-training (Stage 2+)
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### Limitations
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- Not optimized for reasoning (handled in later stages)
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- May struggle with multi-step logical or mathematical problems
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- Trained only on English datasets
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---
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## 📊 Training Data
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This model was trained on the dataset:
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👉 [**Shekswess/trlm-sft-stage-1-final**](https://huggingface.co/datasets/Shekswess/trlm-sft-stage-1-final)
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**Dataset summary**:
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- **Entries**: 58,000
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- **Sources**: 7 HuggingFaceTB/smoltalk2 subsets
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- **Focus**: Non-reasoning conversations and instruction-following
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| Source Dataset | Entries | Percentage % |
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|----------------|---------|---|
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| smoltalk_smollm3_smol_magpie_ultra_no_think | 33,500 | 57.8% |
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| smoltalk_smollm3_smol_summarize_no_think | 7,500 | 12.9% |
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| smoltalk_smollm3_smol_rewrite_no_think | 7,500 | 12.9% |
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| smoltalk_smollm3_systemchats_30k_no_think | 2,500 | 4.3% |
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| smoltalk_smollm3_explore_instruct_rewriting_no_think | 2,500 | 4.3% |
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| tulu_3_sft_personas_instruction_following_no_think | 2,500 | 4.3% |
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| smoltalk_smollm3_everyday_conversations_no_think | 2,000 | 3.4% |
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---
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## ⚙️ Training Procedure
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### Training Hyperparameters
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- **Learning rate**: 3e-4
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- **Train batch size**: 32
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- **Eval batch size**: 8
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- **Gradient accumulation steps**: 4
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- **Total effective batch size**: 128
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- **Optimizer**: AdamW (betas=(0.9, 0.99), eps=1e-08)
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- **LR Scheduler**: Cosine with warmup ratio 0.1
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- **Epochs**: 2
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- **Seed**: 42
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### Framework Versions
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- **Transformers**: 4.56.2
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- **PyTorch**: 2.7.1+rocm7.0.0.git698b58a9
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- **Datasets**: 4.0.0
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- **Tokenizers**: 0.22.1
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---
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## 🚀 Usage
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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model_name = "Shekswess/trlm-stage-1-sft-final-2"
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# Load tokenizer & model
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name)
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# Example inference
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inputs = tokenizer("Write a short daily affirmation:", return_tensors="pt")
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outputs = model.generate(**inputs, max_new_tokens=50)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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## 📌 Next Steps
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- **Stage 2**: Supervised fine-tuning with reasoning-focused data
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- **Stage 3**: DPO / preference optimization for reasoning stability
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---
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Part of the Tiny Reasoning Language Model (trlm) post-training pipeline.
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chat_template.jinja
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{% for message in messages %}
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{% if loop.first and messages[0]['role'] != 'system' %}
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{{ '<|im_start|>system\nYou are a helpful AI assistant named Tiny Reasoning Language Model, trained by Shekswess.<|im_end|>\n' }}
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{% endif %}
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{{ '<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>\n' }}
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{% endfor %}
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{% if add_generation_prompt %}
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{{ '<|im_start|>assistant\n' }}
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{% endif %}
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config.json
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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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"dtype": "bfloat16",
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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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"is_llama_config": true,
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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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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_interleaved": false,
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"rope_scaling": null,
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"rope_theta": 100000,
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"tie_word_embeddings": true,
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"vocab_size": 49152
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vocab.json
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vocab.json
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Block a user