Instructions to use KotshinZ/gpt2-RMT-2-mem512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KotshinZ/gpt2-RMT-2-mem512 with Transformers:
# Load model directly from transformers import RecurrentMemoryTransformer model = RecurrentMemoryTransformer.from_pretrained("KotshinZ/gpt2-RMT-2-mem512", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 3,592 Bytes
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"activation_function": "gelu_new",
"align": "left",
"architectures": [
"RecurrentMemoryTransformer"
],
"attn_pdrop": 0.1,
"base_model_config": {
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"_name_or_path": "openai-community/gpt2",
"activation_function": "gelu_new",
"add_cross_attention": false,
"architectures": [
"GPT2LMHeadModel"
],
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"bad_words_ids": null,
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"cross_attention_hidden_size": null,
"decoder_start_token_id": null,
"diversity_penalty": 0.0,
"do_sample": false,
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"embd_pdrop": 0.1,
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"finetuning_task": null,
"forced_bos_token_id": null,
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"id2label": {
"0": "LABEL_0",
"1": "LABEL_1"
},
"initializer_range": 0.02,
"is_decoder": false,
"is_encoder_decoder": false,
"label2id": {
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"LABEL_1": 1
},
"layer_norm_epsilon": 1e-05,
"length_penalty": 1.0,
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"min_length": 0,
"model_type": "gpt2",
"n_ctx": 1024,
"n_embd": 768,
"n_head": 12,
"n_inner": null,
"n_layer": 12,
"n_positions": 1024,
"no_repeat_ngram_size": 0,
"num_beam_groups": 1,
"num_beams": 1,
"num_return_sequences": 1,
"output_attentions": false,
"output_hidden_states": false,
"output_scores": false,
"pad_token_id": null,
"prefix": null,
"problem_type": null,
"pruned_heads": {},
"remove_invalid_values": false,
"reorder_and_upcast_attn": false,
"repetition_penalty": 1.0,
"resid_pdrop": 0.1,
"return_dict": true,
"return_dict_in_generate": false,
"scale_attn_by_inverse_layer_idx": false,
"scale_attn_weights": true,
"sep_token_id": null,
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"summary_first_dropout": 0.1,
"summary_proj_to_labels": true,
"summary_type": "cls_index",
"summary_use_proj": true,
"suppress_tokens": null,
"task_specific_params": {
"text-generation": {
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"max_length": 50
}
},
"temperature": 1.0,
"tf_legacy_loss": false,
"tie_encoder_decoder": false,
"tie_word_embeddings": true,
"tokenizer_class": null,
"top_k": 50,
"top_p": 1.0,
"torch_dtype": "bfloat16",
"torchscript": false,
"typical_p": 1.0,
"use_bfloat16": false,
"use_cache": false,
"vocab_size": 50257
},
"base_model_type": "gpt2",
"bos_token_id": 50256,
"embd_pdrop": 0.1,
"eos_token_id": 50256,
"initializer_range": 0.02,
"input_seg_len": 512,
"is_memory_all": false,
"layer_norm_epsilon": 1e-05,
"max_n_segments": 2,
"memory_size": 512,
"model_type": "rmt",
"n_ctx": 1024,
"n_embd": 768,
"n_head": 12,
"n_inner": null,
"n_layer": 12,
"n_positions": 1024,
"num_mem_tokens": 10,
"output_seg_len": 512,
"reorder_and_upcast_attn": false,
"resid_pdrop": 0.1,
"scale_attn_by_inverse_layer_idx": false,
"scale_attn_weights": true,
"summary_activation": null,
"summary_first_dropout": 0.1,
"summary_proj_to_labels": true,
"summary_type": "cls_index",
"summary_use_proj": true,
"task_specific_params": {
"text-generation": {
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"max_length": 50
}
},
"torch_dtype": "bfloat16",
"transformers_version": "4.50.0.dev0",
"use_cache": false,
"vocab_size": 50257
}
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