fix: use absolute CDN URLs for images to fix rendering

README.md

@@ -59,45 +59,45 @@ The corpus was constructed through an eight-stage pipeline:
 8. **Split + pack** - deterministic hash-keyed train/val/test split, then SentencePiece BPE
    tokenization into packed uint16 shards for training
 
-![Pipeline Funnel](images/pipeline_funnel.png)
+![Pipeline Funnel](https://huggingface.co/datasets/tonibirat/neBrahma-Nepali-Pretrain-Corpus/resolve/main/images/pipeline_funnel.png)
 
 ### Source Composition and Keep Rates
 
-![Source Keep Rates](images/source_keep_rates.png)
+![Source Keep Rates](https://huggingface.co/datasets/tonibirat/neBrahma-Nepali-Pretrain-Corpus/resolve/main/images/source_keep_rates.png)
 
 ### Quality Filter Gate Analysis
 
 The chart below shows the top rejection gates (gates overlap - a document may fail multiple).
 
-![Quality Gates](images/quality_gates.png)
+![Quality Gates](https://huggingface.co/datasets/tonibirat/neBrahma-Nepali-Pretrain-Corpus/resolve/main/images/quality_gates.png)
 
 ### Document Length Distribution
 
 Distribution of document lengths (in characters) across the quality-filtered corpus
 (sampled from 200K documents).
 
-![Document Length Distribution](images/doc_length_dist.png)
+![Document Length Distribution](https://huggingface.co/datasets/tonibirat/neBrahma-Nepali-Pretrain-Corpus/resolve/main/images/doc_length_dist.png)
 
 ### Devanagari Ratio Distribution
 
 All retained documents have Devanagari ratio = 1.0 (pure script, no Latin contamination).
 
-![Devanagari Ratio](images/devanagari_ratio_dist.png)
+![Devanagari Ratio](https://huggingface.co/datasets/tonibirat/neBrahma-Nepali-Pretrain-Corpus/resolve/main/images/devanagari_ratio_dist.png)
 
 ### Character Category Breakdown
 
-![Character Categories](images/char_categories.png)
+![Character Categories](https://huggingface.co/datasets/tonibirat/neBrahma-Nepali-Pretrain-Corpus/resolve/main/images/char_categories.png)
 
 ### Top-100 Nepali Words by Frequency
 
-![Top 100 Nepali Words](images/word_freq_top100.png)
+![Top 100 Nepali Words](https://huggingface.co/datasets/tonibirat/neBrahma-Nepali-Pretrain-Corpus/resolve/main/images/word_freq_top100.png)
 
 ### Token Zipf Distribution
 
 Vocabulary frequency distribution follows the expected Zipfian curve.
 32,000-token BPE vocabulary with 97.16% coverage (31,091 of 32,000 tokens seen in corpus).
 
-![Token Zipf Distribution](images/token_zipf.png)
+![Token Zipf Distribution](https://huggingface.co/datasets/tonibirat/neBrahma-Nepali-Pretrain-Corpus/resolve/main/images/token_zipf.png)
 
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