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Model: tweijie/tinyllama-medical-merged
Source: Original Platform

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
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+*.bz2 filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+license: apache-2.0
+base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
+tags:
+  - text-generation
+  - lora
+  - peft
+  - merged
+  - medical
+  - fine-tuned
+datasets:
+  - BI55/MedText
+language:
+  - en
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+# TinyLlama-1.1B — Medical QLoRA (Merged)
+
+A QLoRA fine-tuned variant of [TinyLlama-1.1B-intermediate-step-1431k-3T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T), trained on medical question-answering data. The LoRA adapter has been merged into the base weights, so this repo is a standalone model — no separate adapter loading required.
+
+## ⚠️ Intended use
+
+This model was trained as part of a **GenAI training lab** to demonstrate the fine-tuning → merge → deploy workflow. It is **not validated for real clinical or medical use** and should not be used to inform actual medical decisions. Treat its outputs as educational examples of what a small fine-tuned LLM can produce, not medical advice.
+
+## Training details
+
+- **Base model:** `TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T`
+- **Method:** QLoRA (4-bit NF4 quantization during training) via `peft` + `trl.SFTTrainer`
+- **LoRA config:** `r=8`, `lora_alpha=16`
+- **Dataset:** [`BI55/MedText`](https://huggingface.co/datasets/BI55/MedText) — medical case/question-answer pairs
+- **Steps:** 400
+- **Merge:** adapter merged into the base model via `PeftModel.merge_and_unload()`, then saved as a full standalone model
+
+## How to use
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+
+repo_id = "tweijie/tinyllama-medical-merged"
+
+model = AutoModelForCausalLM.from_pretrained(repo_id)
+tokenizer = AutoTokenizer.from_pretrained(repo_id)
+
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, max_length=200)
+prompt = "<s>[INST] A patient presents with restless leg sensations at night. What could be the cause? [/INST]"
+print(pipe(prompt)[0]["generated_text"])
+
+
+Limitations
+1.1B parameters — small model, prone to hallucination and factual errors, especially on medical content.
+Fine-tuned on a single narrow dataset (400 training steps); not broadly evaluated.
+No safety/alignment tuning beyond the base model's own training.

config.json

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+{
+  "_name_or_path": "TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "head_dim": 64,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 5632,
+  "max_position_embeddings": 2048,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 22,
+  "num_key_value_heads": 4,
+  "pretraining_tp": 1,
+  "quantization_config": {
+    "_load_in_4bit": false,
+    "_load_in_8bit": true,
+    "bnb_4bit_compute_dtype": "float32",
+    "bnb_4bit_quant_storage": "uint8",
+    "bnb_4bit_quant_type": "fp4",
+    "bnb_4bit_use_double_quant": false,
+    "llm_int8_enable_fp32_cpu_offload": false,
+    "llm_int8_has_fp16_weight": false,
+    "llm_int8_skip_modules": null,
+    "llm_int8_threshold": 6.0,
+    "load_in_4bit": false,
+    "load_in_8bit": true,
+    "quant_method": "bitsandbytes"
+  },
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.46.0",
+  "use_cache": false,
+  "vocab_size": 32000
+}

generation_config.json

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+{
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "max_length": 2048,
+  "pad_token_id": 0,
+  "transformers_version": "4.46.0"
+}

model.safetensors

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+size 1232844770

special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
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+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "add_prefix_space": null,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "content": "<s>",
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+      "normalized": false,
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+      "single_word": false,
+      "special": true
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+    "2": {
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+      "lstrip": false,
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+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "legacy": false,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": null,
+  "padding_side": "right",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}