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Model: atenareply/smollm2-135m-noval
Source: Original Platform

.gitattributes

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README.md

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+---
+library_name: transformers
+pipeline_tag: text-generation
+language:
+  - en
+base_model:
+  - HuggingFaceTB/SmolLM2-135M
+datasets:
+  - atenareply/noval-corp-training-corpus
+tags:
+  - smollm2
+  - continued-pretraining
+  - domain-adaptation
+license: apache-2.0
+---
+
+# SmolLM2-135M Noval — Domain CPT
+
+HuggingFaceTB/SmolLM2-135M after Continued Pre-Training on the fictional OMC + Mars Express domain corpus. First-round (135M) proof of the pipeline.
+
+## Overview
+
+- **Stage**: Continued Pre-Training (full fine-tune, CLM)
+- **Lineage**: SmolLM2-135M → **CPT** (this model)
+- **Method**: Continued Pre-Training (next-token, full fine-tune) on a 30/70 mars/orbital interleaved corpus (tokenized + packed).
+- **Domain**: fictional — Orbital Mining Corporation (OMC) technical docs + Mars Express telemetry.
+
+## Training
+
+| | |
+|---|---|
+| Corpus | noval-corp-training-corpus (30% Mars / 70% OMC, packed input_ids) |
+| LR / schedule | 5e-4 cosine, warmup 200 steps |
+| Duration / seq | max_steps 5000, seq 1024, eff_batch 32, T4 fp16 |
+
+## Evaluation
+
+_No task metrics for this checkpoint (intermediate / no-training stage)._
+
+## Intended use & limitations
+
+Domain backbone for the 135M line (knows the domain; not instruction-tuned).
+
+**Limitations:**
+- 135M is intrinsically limited — expectations should be modest.
+- Fictional domain; no chat template / instruction following.
+
+---
+_Card generated by `noval-corp/scripts/gen_model_cards.py` (standardized across the noval-corp model family)._

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
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+  "dtype": "float32",
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+  "head_dim": 64,
+  "hidden_act": "silu",
+  "hidden_size": 576,
+  "initializer_range": 0.041666666666666664,
+  "intermediate_size": 1536,
+  "is_llama_config": true,
+  "max_position_embeddings": 8192,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 9,
+  "num_hidden_layers": 30,
+  "num_key_value_heads": 3,
+  "pad_token_id": null,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_interleaved": false,
+  "rope_parameters": {
+    "rope_theta": 100000,
+    "rope_type": "default"
+  },
+  "tie_word_embeddings": true,
+  "transformers_version": "5.12.1",
+  "use_cache": false,
+  "vocab_size": 49152
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 0,
+  "eos_token_id": 0,
+  "transformers_version": "5.12.1"
+}

last-checkpoint/config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
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+  "attention_dropout": 0.0,
+  "bos_token_id": 0,
+  "dtype": "float32",
+  "eos_token_id": 0,
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+  "hidden_act": "silu",
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+  "intermediate_size": 1536,
+  "is_llama_config": true,
+  "max_position_embeddings": 8192,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 9,
+  "num_hidden_layers": 30,
+  "num_key_value_heads": 3,
+  "pad_token_id": null,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_interleaved": false,
+  "rope_parameters": {
+    "rope_theta": 100000,
+    "rope_type": "default"
+  },
+  "tie_word_embeddings": true,
+  "transformers_version": "5.12.1",
+  "use_cache": false,
+  "vocab_size": 49152
+}

last-checkpoint/generation_config.json

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+  "transformers_version": "5.12.1"
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