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Model: Jinyang23/Seed-AlfWorld-3B Source: Original Platform
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199
README.md
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README.md
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---
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license: other
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license_name: qwen-research
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license_link: https://huggingface.co/Qwen/Qwen2.5-3B-Instruct/blob/main/LICENSE
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language:
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- en
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metrics:
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- accuracy
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base_model:
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- Qwen/Qwen2.5-3B-Instruct
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- agent
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- reinforcement-learning
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- long-horizon
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- embodied-ai
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- self-distillation
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- on-policy-distillation
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- alfworld
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- seed
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- qwen2.5
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---
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# SEED-ALFWorld-3B
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## Overview
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Built with Qwen2.5-3B-Instruct, SEED-ALFWorld-3B is trained for text-based
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embodied interaction in ALFWorld using **SEED** (Self-Evolving On-Policy
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Distillation). Training unfolds in two stages:
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- **Hindsight-skill SFT:** the model learns to analyze a completed trajectory
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and summarize it as a concise, episode-level skill.
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- **Self-evolving on-policy distillation:** in each reinforcement-learning
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iteration, the current policy both acts in the environment and analyzes the
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trajectories it has just collected. The generated skills are used to re-score
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the same sampled actions, providing dense token-level supervision alongside
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GRPO. Once updated, the improved policy takes on both roles in the next
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iteration, allowing its behavior and hindsight supervision to evolve
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together.
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At inference time, the model acts from the standard interaction history alone,
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with no analyzer, skill bank, retrieval module, or additional skill prompt.
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## Key Features
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- **Self-evolving supervision:** policy updates improve both action selection
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and the analyzer used to generate the next round of hindsight skills.
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- **On-policy skill generation:** supervision follows the states, actions, and
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failure modes encountered by the current policy.
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- **Dense token-level credit:** skill-induced log-probability shifts provide
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decision-specific guidance beyond terminal rewards.
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- **No inference overhead:** privileged hindsight skills are used only during
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training and are internalized by the released policy.
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## Performance
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The following results are success rates (%) on the ALFWorld seen test
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split. `Avg.` is the unweighted macro-average over the six task families. An
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asterisk indicates that the method also receives a skill prompt at evaluation;
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SEED does not use skills at evaluation.
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| Method | Pick | Look | Clean | Heat | Cool | Pick2 | Avg. |
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|---|---:|---:|---:|---:|---:|---:|---:|
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| Vanilla | 44.4 | 11.1 | 6.2 | 15.4 | 28.6 | 12.5 | 21.9 |
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| Skill-Prompt* | 51.7 | 66.7 | 48.4 | 0.0 | 4.3 | 10.0 | 28.9 |
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| OPSD | 48.8 | 41.7 | 16.7 | 0.0 | 15.8 | 16.7 | 28.1 |
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| GRPO | 91.2 | 62.5 | 96.2 | 61.9 | 65.0 | 47.4 | 75.0 |
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| Skill-GRPO | 88.9 | 71.4 | 58.8 | 70.6 | 40.7 | 29.2 | 60.2 |
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| Skill-GRPO* | 94.3 | 57.1 | 100.0 | 66.7 | 73.1 | 57.1 | 80.5 |
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| GRPO+OPSD | 100.0 | 82.4 | 85.7 | 75.0 | 70.0 | 60.0 | 81.2 |
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| Skill-SD | 88.2 | 50.0 | 96.2 | 52.4 | 65.0 | 57.9 | 73.4 |
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| RLSD | 87.9 | 75.0 | 90.9 | 75.0 | 73.1 | 68.4 | 79.7 |
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| SDAR | 97.1 | 62.5 | 100.0 | 61.9 | 75.0 | 84.2 | 84.4 |
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| **SEED (ours)** | **100.0** | **100.0** | **100.0** | **100.0** | **70.6** | **80.0** | **91.8** |
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On the ALFWorld unseen split, the same 3B SEED checkpoint reaches an
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86.2 macro-average, compared with 70.9 for the matched GRPO baseline.
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| Method | Pick | Look | Clean | Heat | Cool | Pick2 | Avg. |
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|---|---:|---:|---:|---:|---:|---:|---:|
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| ReAct | 17.4 | 6.7 | 8.8 | 7.4 | 9.1 | 0.0 | 8.2 |
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| GRPO | 73.9 | 60.0 | 82.4 | 59.3 | 72.7 | 76.9 | 70.9 |
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| **SEED (ours)** | **90.4** | **78.3** | **79.5** | **94.3** | **86.2** | **88.2** | **86.2** |
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## Quickstart
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Install the runtime dependencies:
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```bash
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pip install "transformers>=4.37.0" accelerate torch
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```
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Load the checkpoint and generate one ALFWorld action:
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_id = "Jinyang23/Seed-AlfWorld-3B"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype="auto",
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device_map="auto",
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)
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def build_alfworld_prompt(
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task_description,
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step_count,
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history_length,
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action_history,
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current_step,
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current_observation,
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admissible_actions,
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):
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actions = ", ".join(admissible_actions)
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return f"""You are an expert agent operating in the ALFRED Embodied Environment. Your task is
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to: {task_description}
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Prior to this step, you have already taken {step_count} step(s). Below are the most recent
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{history_length} observations and the corresponding actions you took: {action_history}
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You are now at step {current_step} and your current observation is: {current_observation}
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Your admissible actions of the current situation are: [{actions}].
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Now it's your turn to take an action.
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You should first reason step-by-step about the current situation. This reasoning process
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MUST be enclosed within <think> </think> tags.
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Once you've finished your reasoning, you should choose an admissible action for current
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step and present it within <action> </action> tags."""
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prompt = build_alfworld_prompt(
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task_description="put a candle in toilet.",
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step_count=0,
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history_length=0,
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action_history="None.",
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current_step=1,
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current_observation="You are in the middle of a room.",
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admissible_actions=["look", "go to shelf 1", "go to toilet 1"],
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)
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text = tokenizer.apply_chat_template(
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[{"role": "user", "content": prompt}],
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tokenize=False,
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add_generation_prompt=True,
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)
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inputs = tokenizer([text], return_tensors="pt").to(model.device)
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outputs = model.generate(
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**inputs,
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max_new_tokens=512,
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do_sample=False,
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)
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new_tokens = outputs[:, inputs.input_ids.shape[1]:]
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response = tokenizer.batch_decode(new_tokens, skip_special_tokens=True)[0]
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print(response)
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```
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In a complete evaluation loop, replace the example values with the current
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ALFWorld task, recent observation-action history, observation, and admissible
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actions at every step. Only execute the action emitted inside `<action>` tags.
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The model can also be served with vLLM:
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```bash
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vllm serve Jinyang23/Seed-AlfWorld-3B \
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--served-model-name Seed-AlfWorld-3B \
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--dtype bfloat16
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```
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## Limitations
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- The model is specialized for ALFWorld-style text interaction and may not
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transfer reliably to unrelated environments or prompting formats.
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## License
|
||||
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This checkpoint is a derivative of Qwen2.5-3B-Instruct and is distributed under
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||||
the [Qwen Research License Agreement](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct/blob/main/LICENSE).
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||||
## Citation
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||||
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||||
Citation metadata will be added after the public paper release.
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||||
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||||
## Acknowledgements
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||||
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The SEED implementation builds on
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[veRL](https://github.com/volcengine/verl),
|
||||
[verl-agent](https://github.com/langfengQ/verl-agent), and
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[SDAR](https://github.com/ZJU-REAL/SDAR).
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## Links
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||||
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- Model: https://huggingface.co/Jinyang23/Seed-AlfWorld-3B
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- Base model: https://huggingface.co/Qwen/Qwen2.5-3B-Instruct
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- Paper: https://arxiv.org/pdf/2607.14777
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- Code: https://github.com/jinyangwu/SEED
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added_tokens.json
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{
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"</tool_call>": 151658,
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}
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0]['role'] == 'system' %}
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{{- messages[0]['content'] }}
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||||
{%- else %}
|
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{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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||||
{%- endif %}
|
||||
{{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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||||
{%- for tool in tools %}
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||||
{{- "\n" }}
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{{- tool | tojson }}
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||||
{%- endfor %}
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||||
{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
|
||||
{%- else %}
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||||
{%- if messages[0]['role'] == 'system' %}
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||||
{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
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||||
{%- else %}
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||||
{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- for message in messages %}
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||||
{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
|
||||
{%- elif message.role == "assistant" %}
|
||||
{{- '<|im_start|>' + message.role }}
|
||||
{%- if message.content %}
|
||||
{{- '\n' + message.content }}
|
||||
{%- endif %}
|
||||
{%- for tool_call in message.tool_calls %}
|
||||
{%- if tool_call.function is defined %}
|
||||
{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{{- '\n<tool_call>\n{"name": "' }}
|
||||
{{- tool_call.name }}
|
||||
{{- '", "arguments": ' }}
|
||||
{{- tool_call.arguments | tojson }}
|
||||
{{- '}\n</tool_call>' }}
|
||||
{%- endfor %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- elif message.role == "tool" %}
|
||||
{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
|
||||
{{- '<|im_start|>user' }}
|
||||
{%- endif %}
|
||||
{{- '\n<tool_response>\n' }}
|
||||
{{- message.content }}
|
||||
{{- '\n</tool_response>' }}
|
||||
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- if add_generation_prompt %}
|
||||
{{- '<|im_start|>assistant\n' }}
|
||||
{%- endif %}
|
||||
66
config.json
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config.json
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||||
{
|
||||
"architectures": [
|
||||
"Qwen2ForCausalLM"
|
||||
],
|
||||
"attention_dropout": 0.0,
|
||||
"dtype": "bfloat16",
|
||||
"eos_token_id": 151645,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 2048,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 11008,
|
||||
"layer_types": [
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention"
|
||||
],
|
||||
"max_position_embeddings": 32768,
|
||||
"max_window_layers": 70,
|
||||
"model_type": "qwen2",
|
||||
"num_attention_heads": 16,
|
||||
"num_hidden_layers": 36,
|
||||
"num_key_value_heads": 2,
|
||||
"pad_token_id": 151643,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": null,
|
||||
"rope_theta": 1000000.0,
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": true,
|
||||
"transformers_version": "4.57.3",
|
||||
"use_cache": true,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 151936
|
||||
}
|
||||
14
generation_config.json
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generation_config.json
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{
|
||||
"bos_token_id": 151643,
|
||||
"do_sample": true,
|
||||
"eos_token_id": [
|
||||
151645,
|
||||
151643
|
||||
],
|
||||
"pad_token_id": 151643,
|
||||
"repetition_penalty": 1.05,
|
||||
"temperature": 0.7,
|
||||
"top_k": 20,
|
||||
"top_p": 0.8,
|
||||
"transformers_version": "4.57.3"
|
||||
}
|
||||
151388
merges.txt
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151388
merges.txt
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File diff suppressed because it is too large
Load Diff
3
model-00001-of-00002.safetensors
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3
model-00001-of-00002.safetensors
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version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:b967884a4bed1987107585125d8bbf4e3e3c58c5f014080b461d3be61cd41795
|
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size 4995286880
|
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||||
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|
||||
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|
||||
31
special_tokens_map.json
Normal file
31
special_tokens_map.json
Normal file
@@ -0,0 +1,31 @@
|
||||
{
|
||||
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|
||||
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|
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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|
||||
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|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
|
||||
size 11421896
|
||||
207
tokenizer_config.json
Normal file
207
tokenizer_config.json
Normal file
@@ -0,0 +1,207 @@
|
||||
{
|
||||
"add_bos_token": false,
|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
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||||
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|
||||
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|
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
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|
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|
||||
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|
||||
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|
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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||||
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|
||||
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|
||||
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||||
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||||
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|
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user