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huluhuluu/qwen3-1.7b-eagle3-sharegpt-sw768
qwen3-1.7b-eagle3-sharegpt-sw768 is a machine learning model from huluhuluu. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
This repository contains intermediate checkpoints from SpecForge EAGLE3 draft-model training against Qwen3-1.7B. The draft attention uses a causal sliding window of 768 tokens.
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Updated Sep 9, 2026
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From the Hugging Face model README
This repository contains intermediate checkpoints from SpecForge EAGLE3 draft-model training against Qwen3-1.7B. The draft attention uses a causal sliding window of 768 tokens.
Checkpoints are stored in epoch_<epoch>_step_<global_step>/ directories at 5,000-step intervals. Each directory contains:
config.json: draft model configurationmodel.safetensors: draft model weightstraining_state.pt: epoch, global step, optimizer state, scheduler state, and saved training argumentsThis upload contains 88 checkpoints from step 5,000 through step 440,000. The latest local checkpoint at upload time is epoch_9_step_440000.
The checkpoint weights exclude the frozen target embedding weights. SpecForge loads those weights from the target model when training or resuming.
| Parameter | Value |
|---|---|
| Target model | Qwen3-1.7B |
| Framework revision | SpecForge 9fbbde8ab5d6ee69fb0af3701330027b8beca37a |
| Draft architecture | LlamaForCausalLMEagle3 |
| Draft layers | 1 |
| Sliding window | 768 |
| Attention backend | SDPA |
| Target backend | SGLang / FlashInfer |
| Training data | sharegpt_train.jsonl |
| Epochs | 10 |
| Total scheduled steps | 467,800 |
| Latest uploaded step | 440,000 |
| Batch size | 1 |
| Data parallel size | 2 |
| Tensor parallel size | 1 |
| Gradient accumulation | 1 |
| Learning rate | 0.0001 |
| Warmup ratio | 0.015 |
| Maximum gradient norm | 0.5 |
| Maximum sequence length | 2,048 |
| TTT length | 7 |
| Draft vocabulary size | 32,000 |
| Training dtype | bfloat16 |
| Save/evaluation interval | 5,000 steps |
| Log interval | 50 steps |
| Seed | 0 |
target_model_path: /data/HF_MODELS/Qwen3-1.7B
draft_model_config: <workspace-root>/code/test-spec/SpecForge/configs/qwen3-1.7b-eagle3.json
embedding_key: model.embed_tokens.weight
target_model_backend: sglang
train_data_path: /data/HF_MODELS/data/specforge_sharegpt/sharegpt_train.jsonl
train_hidden_states_path: null
eval_data_path: null
eval_hidden_states_path: null
chat_template: qwen
is_preformatted: false
train_only_last_turn: false
build_dataset_num_proc: 16
dataloader_num_workers: 4
num_epochs: 10
max_num_steps: null
total_steps: 467800
batch_size: 1
learning_rate: 0.0001
max_length: 2048
draft_sliding_window: 768
warmup_ratio: 0.015
max_grad_norm: 0.5
ttt_length: 7
draft_accumulation_steps: 1
tp_size: 1
dp_size: 2
sp_ulysses_size: 1
sp_ring_size: 1
attention_backend: sdpa
sglang_attention_backend: flashinfer
sglang_mem_fraction_static: 0.4
sglang_context_length: null
sglang_enable_nccl_nvls: false
sglang_enable_symm_mem: false
sglang_enable_torch_compile: false
sglang_enable_dp_attention: false
sglang_enable_dp_lm_head: false
sglang_enable_piecewise_cuda_graph: false
sglang_piecewise_cuda_graph_max_tokens: 4096
sglang_piecewise_cuda_graph_tokens: null
sglang_ep_size: 1
save_interval: 5000
eval_interval: 5000
log_interval: 50
seed: 0
trust_remote_code: false
is_vlm: false
report_to: none
</details>
These are SpecForge EAGLE3 draft checkpoints, not standalone causal language models. Load them with the matching SpecForge draft-model implementation and the Qwen3-1.7B target model.