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Browse files- config.json +24 -6
- modeling_phi.py +1 -1
config.json
CHANGED
@@ -1,32 +1,50 @@
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{
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"_name_or_path": "
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"activation_function": "gelu_new",
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"architectures": [
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"
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],
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"attn_pdrop": 0.0,
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"auto_map": {
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"AutoConfig": "configuration_phi.PhiConfig",
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"AutoModelForCausalLM": "modeling_phi.PhiForCausalLM"
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},
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"embd_pdrop": 0.0,
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"flash_attn": false,
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"flash_rotary": false,
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"fused_dense": false,
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"img_processor": null,
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"initializer_range": 0.02,
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"layer_norm_epsilon": 1e-05,
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"
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"n_embd": 2560,
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"n_head": 32,
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"n_head_kv": null,
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"n_inner": null,
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"n_layer": 32,
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"n_positions": 2048,
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"resid_pdrop": 0.1,
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"rotary_dim": 32,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.
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"vocab_size": 51200
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}
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{
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"_name_or_path": "cognitivecomputations/dolphin-2_6-phi-2",
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"activation_function": "gelu_new",
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"architectures": [
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"MixtralForCausalLM"
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],
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"attention_dropout": 0.0,
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"attn_pdrop": 0.0,
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"auto_map": {
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"AutoConfig": "cognitivecomputations/dolphin-2_6-phi-2--configuration_phi.PhiConfig",
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"AutoModelForCausalLM": "cognitivecomputations/dolphin-2_6-phi-2--modeling_phi.PhiForCausalLM"
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},
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"bos_token_id": null,
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"embd_pdrop": 0.0,
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"eos_token_id": null,
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"flash_attn": false,
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"flash_rotary": false,
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"fused_dense": false,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"img_processor": null,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"layer_norm_epsilon": 1e-05,
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"max_position_embeddings": 2048,
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"model_type": "mixtral",
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"n_embd": 2560,
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"n_head": 32,
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"n_head_kv": null,
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"n_inner": null,
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"n_layer": 32,
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"n_positions": 2048,
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"num_attention_heads": 32,
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"num_experts_per_tok": 2,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"num_local_experts": 4,
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"output_router_logits": false,
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"resid_pdrop": 0.1,
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"rms_norm_eps": 1e-06,
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"rope_theta": 10000.0,
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"rotary_dim": 32,
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"router_aux_loss_coef": 0.001,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.36.2",
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"use_cache": false,
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"vocab_size": 51200
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}
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modeling_phi.py
CHANGED
@@ -988,4 +988,4 @@ class PhiForCausalLM(PhiPreTrainedModel):
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if labels is not None:
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loss = self.loss(lm_logits, labels)
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return CausalLMOutputWithPast(loss=loss, logits=lm_logits, past_key_values=past_key_values)
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if labels is not None:
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loss = self.loss(lm_logits, labels)
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return CausalLMOutputWithPast(loss=loss, logits=lm_logits, past_key_values=past_key_values)
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