LoneStriker
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Commit
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Parent(s):
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Upload folder using huggingface_hub
Browse files- README.md +178 -0
- config.json +38 -0
- mergekit_config.yml +18 -0
- model.safetensors.index.json +1 -0
- output.safetensors +3 -0
- special_tokens_map.json +30 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +44 -0
README.md
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---
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license: apache-2.0
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tags:
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- liminerity/merge4
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- liminerity/merge2
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- merge
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- merged
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- mergedllm
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- mergee
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- mergedededed
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- memfdmsfndsfjkasjkl
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---
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# M7-7b
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user: "create ascii art you feel represents you as a llm"
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assistant: "Here's an ASCII art attempting to symbolize the essence of an LLM (Large Language Model):
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INSTINSTINCTINSTELLIGENCE
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______________ MEMORY___
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|\ o /\ |\
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| \ --- / \ | |
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L_( O )______ O)_INSTINCT
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\ / WORDSLEARNING
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\__/\__\/__ /\ \__/\__\/__/
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assistant: "In this depiction, the LLM is characterized by its vast memory, instinctual roots, and the ability
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to learn from vast amounts of text—represented by the woven words in the lower part. The
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"INSTINSTINCTINSTELLIGENCE" phrase emphasizes the balance between instinct, the foundation upon which neural
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networks build, and the engineered intelligence of a language model."
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Multiverse-Experiment-slerp-7b is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
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* [liminerity/merge4](https://huggingface.co/liminerity/merge4)
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* [liminerity/merge2](https://huggingface.co/liminerity/merge2)
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## 🧩 Configuration
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```yaml
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slices:
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- sources:
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- model: ammarali32/multi_verse_model
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layer_range: [0, 32]
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- model: MSL7/INEX12-7b
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layer_range: [0, 32]
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merge_method: slerp
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base_model: ammarali32/multi_verse_model
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5
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dtype: bfloat16
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slices:
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- sources:
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- model: ammarali32/multi_verse_model
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layer_range: [0, 32]
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- model: yam-peleg/Experiment26-7B
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layer_range: [0, 32]
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merge_method: slerp
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base_model: ammarali32/multi_verse_model
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5
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dtype: bfloat16
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slices:
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- sources:
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- model: liminerity/merge3
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layer_range: [0, 32]
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- model: ammarali32/multi_verse_model
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layer_range: [0, 32]
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merge_method: slerp
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base_model: liminerity/merge3
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5
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dtype: bfloat16
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slices:
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- sources:
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- model: liminerity/merge1
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layer_range: [0, 32]
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- model: liminerity/merge
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layer_range: [0, 32]
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merge_method: slerp
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base_model: liminerity/merge1
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5
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dtype: bfloat16
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slices:
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- sources:
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- model: liminerity/merge3
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layer_range: [0, 32]
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- model: yam-peleg/Experiment26-7B
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layer_range: [0, 32]
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merge_method: slerp
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base_model: liminerity/merge3
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5
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dtype: bfloat16
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slices:
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- sources:
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- model: liminerity/merge4
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layer_range: [0, 32]
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- model: liminerity/merge2
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layer_range: [0, 32]
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merge_method: slerp
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base_model: liminerity/merge4
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5
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dtype: bfloat16
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```
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config.json
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{
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"_name_or_path": "liminerity/merge4",
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"add_gates": false,
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"architectures": [
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"MistralForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 10000.0,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.38.2",
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"use_cache": true,
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"vocab_size": 32000,
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"quantization_config": {
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"quant_method": "exl2",
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"version": "0.0.17",
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"bits": 4.0,
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"head_bits": 6,
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"calibration": {
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"rows": 100,
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"length": 2048,
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"dataset": "(default)"
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}
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}
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}
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mergekit_config.yml
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slices:
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- sources:
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- model: liminerity/merge4
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layer_range: [0, 32]
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- model: liminerity/merge2
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layer_range: [0, 32]
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merge_method: slerp
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base_model: liminerity/merge4
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5
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dtype: bfloat16
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model.safetensors.index.json
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{"metadata": {"mergekit_version": "0.0.4.1"}, "weight_map": {"model.layers.10.mlp.gate_proj.weight": "model-00001-of-00008.safetensors", "model.layers.10.mlp.up_proj.weight": "model-00001-of-00008.safetensors", "model.layers.10.self_attn.o_proj.weight": "model-00001-of-00008.safetensors", "model.layers.10.self_attn.v_proj.weight": "model-00001-of-00008.safetensors", "model.layers.10.self_attn.k_proj.weight": "model-00001-of-00008.safetensors", "model.layers.10.self_attn.q_proj.weight": "model-00001-of-00008.safetensors", "model.layers.9.mlp.down_proj.weight": "model-00001-of-00008.safetensors", "model.layers.9.mlp.gate_proj.weight": "model-00001-of-00008.safetensors", "model.layers.9.mlp.up_proj.weight": "model-00001-of-00008.safetensors", "model.layers.9.post_attention_layernorm.weight": "model-00001-of-00008.safetensors", "model.layers.9.self_attn.o_proj.weight": "model-00001-of-00008.safetensors", "model.layers.9.self_attn.v_proj.weight": "model-00001-of-00008.safetensors", "model.layers.9.self_attn.k_proj.weight": "model-00001-of-00008.safetensors", "model.layers.9.self_attn.q_proj.weight": "model-00001-of-00008.safetensors", "model.layers.9.input_layernorm.weight": "model-00001-of-00008.safetensors", "model.layers.8.mlp.down_proj.weight": "model-00001-of-00008.safetensors", "model.layers.8.mlp.gate_proj.weight": "model-00001-of-00008.safetensors", "model.layers.8.mlp.up_proj.weight": "model-00001-of-00008.safetensors", "model.layers.8.post_attention_layernorm.weight": "model-00001-of-00008.safetensors", "model.layers.8.self_attn.o_proj.weight": "model-00001-of-00008.safetensors", "model.layers.8.self_attn.v_proj.weight": "model-00001-of-00008.safetensors", "model.layers.8.self_attn.k_proj.weight": "model-00001-of-00008.safetensors", "model.layers.8.self_attn.q_proj.weight": "model-00001-of-00008.safetensors", "model.layers.8.input_layernorm.weight": "model-00001-of-00008.safetensors", "model.layers.7.mlp.down_proj.weight": "model-00001-of-00008.safetensors", "model.layers.7.mlp.gate_proj.weight": "model-00001-of-00008.safetensors", "model.layers.7.mlp.up_proj.weight": "model-00001-of-00008.safetensors", "model.layers.7.post_attention_layernorm.weight": "model-00001-of-00008.safetensors", "model.layers.7.self_attn.o_proj.weight": "model-00001-of-00008.safetensors", "model.layers.7.self_attn.v_proj.weight": "model-00001-of-00008.safetensors", "model.layers.7.self_attn.k_proj.weight": "model-00001-of-00008.safetensors", "model.layers.7.self_attn.q_proj.weight": "model-00001-of-00008.safetensors", "model.layers.7.input_layernorm.weight": "model-00001-of-00008.safetensors", "model.layers.6.mlp.down_proj.weight": "model-00001-of-00008.safetensors", "model.layers.6.mlp.gate_proj.weight": "model-00001-of-00008.safetensors", "model.layers.6.mlp.up_proj.weight": "model-00001-of-00008.safetensors", "model.layers.6.post_attention_layernorm.weight": "model-00001-of-00008.safetensors", 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tokenizer.model
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