初始化项目，由ModelHub XC社区提供模型
Model: Stinger2311/hail-mary-inspired-student-merged Source: Original Platform
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*.7z filter=lfs diff=lfs merge=lfs -text
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104
README.md
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README.md
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---
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language:
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- en
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pipeline_tag: text-generation
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library_name: transformers
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license: apache-2.0
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base_model: Qwen/Qwen2.5-3B-Instruct
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tags:
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- qwen2.5
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- merged-model
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- sci-fi
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- instruction-tuning
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- educational
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model-index:
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- name: hail-mary-inspired-student-merged
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results: []
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---
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# Hail Mary Inspired Student (Merged)
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This is a merged, full-weight model produced from:
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- Base model: `Qwen/Qwen2.5-3B-Instruct`
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- LoRA adapter: `Stinger2311/hail-mary-inspired-student-lora`
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The objective is a calm, science-literate assistant style inspired by first-contact and high-uncertainty problem-solving themes, trained on original (public-safe) instruction data.
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## Intended use
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- Educational demos and portfolio projects
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- Prompted reasoning and explanation tasks
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- Lightweight experiments with a themed assistant persona
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## Not intended use
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- High-stakes decisions (medical, legal, safety-critical)
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- Claims of factual authority without external verification
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- Any official franchise affiliation or licensed reproduction
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## Quickstart (Transformers)
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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model_id = "Stinger2311/hail-mary-inspired-student-merged"
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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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dtype=torch.float16,
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device_map="auto",
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)
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prompt = (
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"System: You are a calm, science-literate assistant. "
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"Be explicit about uncertainty when evidence is incomplete.\n\n"
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"User: How should a crew handle uncertainty during first contact?\n\n"
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"Assistant:"
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)
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inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
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with torch.no_grad():
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out = model.generate(
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**inputs,
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max_new_tokens=180,
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temperature=0.7,
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top_p=0.9,
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do_sample=True,
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)
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reply_ids = out[0][inputs["input_ids"].shape[-1]:]
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print(tokenizer.decode(reply_ids, skip_special_tokens=True))
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```
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## Prompting tips
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- Use an explicit system instruction for tone and uncertainty handling.
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- Ask for structured outputs when you need consistency.
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- For safer behavior, request assumptions and confidence levels in the response.
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## Training lineage
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This merged model comes from a LoRA fine-tuning workflow using:
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- Original seed + synthetic reviewed instruction data
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- Unsloth/QLoRA style tuning workflow
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- Adapter merge into full weights for easier deployment
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Related assets:
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- Adapter model: `Stinger2311/hail-mary-inspired-student-lora`
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- Dataset: `Stinger2311/hail-mary-inspired-sci-fi-instruct`
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- Source repo: `https://github.com/Chandan062311/Hail-Mary`
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## Limitations
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- May hallucinate scientific details.
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- Performance depends heavily on prompt quality.
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- Not benchmarked for safety-critical production use.
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## Safety note
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Outputs should be reviewed by a human before use in consequential contexts. For public demos, present this model as an educational themed assistant, not an authority system.
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54
chat_template.jinja
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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 %}
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{{- "\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" }}
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{%- 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' }}
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{%- endif %}
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{%- endif %}
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{%- 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) %}
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{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{{- '<|im_start|>' + message.role }}
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{%- if message.content %}
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{{- '\n' + message.content }}
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{%- endif %}
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{%- for tool_call in message.tool_calls %}
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{%- if tool_call.function is defined %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '\n<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{{- tool_call.arguments | tojson }}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{{- '<|im_end|>\n' }}
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{%- elif message.role == "tool" %}
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{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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{{- message.content }}
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{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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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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config.json
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{
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"architectures": [
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"Qwen2ForCausalLM"
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"dtype": "float16",
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"eos_token_id": 151645,
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"hidden_size": 2048,
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"layer_types": [
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"full_attention",
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"full_attention"
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],
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"max_position_embeddings": 32768,
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"max_window_layers": 70,
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"model_type": "qwen2",
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"num_attention_heads": 16,
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"rms_norm_eps": 1e-06,
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"rope_parameters": {
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"rope_type": "default"
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},
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"sliding_window": null,
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"tie_word_embeddings": true,
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"transformers_version": "5.4.0",
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"use_cache": true,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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14
generation_config.json
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generation_config.json
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"repetition_penalty": 1.05,
|
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"temperature": 0.7,
|
||||
"top_k": 20,
|
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"top_p": 0.8,
|
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"transformers_version": "5.4.0"
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Normal file
15
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Normal file
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"backend": "tokenizers",
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"is_local": false,
|
||||
"model_max_length": 32768,
|
||||
"pad_token": "<|PAD_TOKEN|>",
|
||||
"padding_side": "left",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
Reference in New Issue
Block a user