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Model: Raghav-Singhal/tulu3sft-normal-smollm-1p7b-500B-30n-2048sl-960gbsz
Source: Original Platform

README.md

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+---
+language: en
+license: apache-2.0
+tags:
+  - smollm
+  - llama
+  - causal-lm
+  - sft
+  - tulu
+model_type: llama
+pipeline_tag: text-generation
+---
+
+# tulu3sft-normal-smollm-1p7b-500B-30n-2048sl-960gbsz
+
+This is a supervised fine-tuned (SFT) checkpoint for a SmolLM2-style 1.7B model,
+trained on the `allenai/tulu-3-sft-mixture` dataset. It is based on the 500B-token
+pretrained base checkpoint and exported in Hugging Face `LlamaForCausalLM` format.
+
+## Details
+
+- Base model: `normal-smollm-1p7b-500B-30n-2048sl-960gbsz`
+- SFT dataset: `allenai/tulu-3-sft-mixture`
+- Context length: 2048
+- Vocab size: 49152
+- Architecture: Llama (RMSNorm, SwiGLU, RoPE)
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "REPLACE_WITH_OWNER/tulu3sft-normal-smollm-1p7b-500B-30n-2048sl-960gbsz"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
+```
+
+## Notes
+
+This is an SFT model intended for chat-style use. For preference tuning, run DPO
+on top of this checkpoint.