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Model: MohitM2/sruti-1.5b
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen2.5-1.5B
+language:
+  - en
+  - sa
+tags:
+  - hinduism
+  - vedanta
+  - sanskrit
+  - philosophy
+  - qwen2
+pipeline_tag: text-generation
+---
+
+# Śruti 1.5B
+
+Śruti is a guide to Hindu / Sanātana / Vedic / Vedāntic philosophy — the Vedas, Upaniṣads,
+Bhagavad Gītā, Purāṇas, the six darśanas, Yoga, Tantra, and the Bhakti traditions. It answers
+in clear English and, where relevant, quotes the original Sanskrit (Devanāgarī with IAST
+transliteration) with translation and source.
+
+Built by fine-tuning **Qwen2.5-1.5B** (Apache-2.0) with LoRA on hand-authored Q&A covering the
+core texts and schools, curated alongside a ~19M-token corpus of primary sources (Vedas,
+Upaniṣads, 13 Purāṇas, the epics, Dharmaśāstra, darśana literature, Yoga, Tantra, and modern
+expositors such as Dasgupta and Vivekananda).
+
+## Usage
+
+### transformers
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+repo = "MohitM2/sruti-1.5b"
+tok = AutoTokenizer.from_pretrained(repo)
+model = AutoModelForCausalLM.from_pretrained(repo, torch_dtype="auto")
+
+messages = [
+    {"role": "system", "content": "You are Śruti, a knowledgeable and reverent guide to Hindu philosophy."},
+    {"role": "user", "content": "What is the ātman according to Vedānta?"},
+]
+inputs = tok.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt")
+out = model.generate(inputs, max_new_tokens=400, temperature=0.7, top_p=0.9)
+print(tok.decode(out[0][inputs.shape[-1]:], skip_special_tokens=True))
+```
+
+### Ollama (GGUF)
+
+Quantized GGUF files are in the [`gguf/`](./tree/main/gguf) folder (Q4_K_M ≈ 0.9 GB,
+Q8_0 ≈ 1.5 GB). With a Modelfile using the Qwen2.5 chat template:
+
+```
+ollama create sruti -f Modelfile
+ollama run sruti "What is the atman according to Vedanta?"
+```
+
+## Training
+
+- **Base:** Qwen/Qwen2.5-1.5B
+- **Method:** LoRA (r=64, α=128) on all attention + MLP projections, merged into the base
+- **Data:** hand-authored instruction Q&A on Hindu philosophy with Sanskrit citations
+- **Precision:** fp16; trained on a single NVIDIA T4/P100 (Kaggle)
+
+## Limitations
+
+A 1.5B-parameter model: it can misquote, oversimplify contested doctrinal points, or
+hallucinate citations despite training against it. Verify Sanskrit quotations and sources
+before scholarly use. Not a substitute for study with primary texts or qualified teachers.

added_tokens.json

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config.json

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+{
+  "_name_or_path": "Qwen/Qwen2.5-1.5B-Instruct",
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
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+  "hidden_act": "silu",
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+  "max_position_embeddings": 32768,
+  "max_window_layers": 21,
+  "model_type": "qwen2",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 2,
+  "rms_norm_eps": 1e-06,
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+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "torch_dtype": "float16",
+  "transformers_version": "4.45.2",
+  "use_cache": false,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

generation_config.json

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+  "temperature": 0.7,
+  "top_k": 20,
+  "top_p": 0.8,
+  "transformers_version": "4.45.2"
+}

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+}