ca9203e0b5e26f50400116c2a970104732489b9b
Model: Raghav-Singhal/tulu3sft-normal-smollm-1p7b-500B-30n-2048sl-960gbsz Source: Original Platform
language, license, tags, model_type, pipeline_tag
| language | license | tags | model_type | pipeline_tag | |||||
|---|---|---|---|---|---|---|---|---|---|
| en | apache-2.0 |
|
llama | 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
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.
Description
Model synced from source: Raghav-Singhal/tulu3sft-normal-smollm-1p7b-500B-30n-2048sl-960gbsz
Languages
Jinja
100%