Upload 7 files
Browse files- README.md +33 -3
- config.json +12 -0
- model.safetensors +3 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +7 -0
- tokenizer_config.json +58 -0
- vocab.txt +0 -0
README.md
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# Snowflake-G0-Release
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This is the initial release of the Snowflake series language models, trained on the DialogMLM-50K dataset with optimized memory usage.
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## Model details
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- Architecture: SnowflakeCore
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- Hidden size: 384
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- Number of attention heads: 6
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- Number of layers: 4
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- Feed-forward dimension: 768
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- Maximum sequence length: 384
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- Vocabulary size: 30522
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## HuggingFace Transformers Compatibility
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This model is fully compatible with the HuggingFace Transformers library. You can load it using:
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```python
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from transformers import AutoConfig, AutoModel, AutoTokenizer
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tokenizer = AutoTokenizer.from_pretrained("path/to/snowflake_g0_release")
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config = AutoConfig.from_pretrained("path/to/snowflake_g0_release")
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model = AutoModel.from_pretrained("path/to/snowflake_g0_release")
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```
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## Memory Optimization Techniques
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- Mixed precision training
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- Gradient accumulation (4 steps)
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- Fused QKV projection
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- Pre-norm architecture
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- Weight tying between embedding and output layers
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- Half-precision model storage
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The model weights are stored in both PyTorch (.bin) and safetensors format for improved security, loading efficiency, and compatibility.
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config.json
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{
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"architectures": [
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"SnowflakeCore"
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],
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"hidden_size": 384,
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"intermediate_size": 768,
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"max_position_embeddings": 384,
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"num_attention_heads": 6,
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"num_hidden_layers": 4,
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"transformers_version": "4.51.3",
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"vocab_size": 30522
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:71cc42d8dfe014ef49409730a63eb30e085822c768360f8263b9c0428372086d
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size 33274540
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:1bb569d5315b86cd6109c43c565f3400e3127765ffa7fe7c8ca9f53b757377a1
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size 66559270
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special_tokens_map.json
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{
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"cls_token": "[CLS]",
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"mask_token": "[MASK]",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"unk_token": "[UNK]"
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}
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tokenizer_config.json
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{
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"added_tokens_decoder": {
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"0": {
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"content": "[PAD]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"100": {
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"content": "[UNK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"101": {
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"content": "[CLS]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"102": {
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"content": "[SEP]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"103": {
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"content": "[MASK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_basic_tokenize": true,
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"do_lower_case": true,
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"extra_special_tokens": {},
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"never_split": null,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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}
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vocab.txt
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