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Model: Stinger2311/hail-mary-inspired-student-merged
Source: Original Platform

README.md

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+---
+language:
+  - en
+pipeline_tag: text-generation
+library_name: transformers
+license: apache-2.0
+base_model: Qwen/Qwen2.5-3B-Instruct
+tags:
+  - qwen2.5
+  - merged-model
+  - sci-fi
+  - instruction-tuning
+  - educational
+model-index:
+  - name: hail-mary-inspired-student-merged
+    results: []
+---
+
+# Hail Mary Inspired Student (Merged)
+
+This is a merged, full-weight model produced from:
+
+- Base model: `Qwen/Qwen2.5-3B-Instruct`
+- LoRA adapter: `Stinger2311/hail-mary-inspired-student-lora`
+
+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.
+
+## Intended use
+
+- Educational demos and portfolio projects
+- Prompted reasoning and explanation tasks
+- Lightweight experiments with a themed assistant persona
+
+## Not intended use
+
+- High-stakes decisions (medical, legal, safety-critical)
+- Claims of factual authority without external verification
+- Any official franchise affiliation or licensed reproduction
+
+## Quickstart (Transformers)
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "Stinger2311/hail-mary-inspired-student-merged"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    dtype=torch.float16,
+    device_map="auto",
+)
+
+prompt = (
+    "System: You are a calm, science-literate assistant. "
+    "Be explicit about uncertainty when evidence is incomplete.\n\n"
+    "User: How should a crew handle uncertainty during first contact?\n\n"
+    "Assistant:"
+)
+
+inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+with torch.no_grad():
+    out = model.generate(
+        **inputs,
+        max_new_tokens=180,
+        temperature=0.7,
+        top_p=0.9,
+        do_sample=True,
+    )
+
+reply_ids = out[0][inputs["input_ids"].shape[-1]:]
+print(tokenizer.decode(reply_ids, skip_special_tokens=True))
+```
+
+## Prompting tips
+
+- Use an explicit system instruction for tone and uncertainty handling.
+- Ask for structured outputs when you need consistency.
+- For safer behavior, request assumptions and confidence levels in the response.
+
+## Training lineage
+
+This merged model comes from a LoRA fine-tuning workflow using:
+
+- Original seed + synthetic reviewed instruction data
+- Unsloth/QLoRA style tuning workflow
+- Adapter merge into full weights for easier deployment
+
+Related assets:
+
+- Adapter model: `Stinger2311/hail-mary-inspired-student-lora`
+- Dataset: `Stinger2311/hail-mary-inspired-sci-fi-instruct`
+- Source repo: `https://github.com/Chandan062311/Hail-Mary`
+
+## Limitations
+
+- May hallucinate scientific details.
+- Performance depends heavily on prompt quality.
+- Not benchmarked for safety-critical production use.
+
+## Safety note
+
+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.