Evan-Lin commited on
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Push model using huggingface_hub.

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - trl
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+ - transformers
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+ - reinforcement-learning
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+ ---
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+
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+ # TRL Model
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+
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+ This is a [TRL language model](https://github.com/lvwerra/trl) that has been fine-tuned with reinforcement learning to
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+ guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.
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+
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+ ## Usage
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+
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+ To use this model for inference, first install the TRL library:
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+
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+ ```bash
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+ python -m pip install trl
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+ ```
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+
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+ You can then generate text as follows:
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+
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+ ```python
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+ from transformers import pipeline
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+
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+ generator = pipeline("text-generation", model="Evan-Lin//tmp/tmpdxnkhvya/Evan-Lin/Bart-Amazon-rougelastbatch1-attractive2-keywordmax1")
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+ outputs = generator("Hello, my llama is cute")
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+ ```
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+
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+ If you want to use the model for training or to obtain the outputs from the value head, load the model as follows:
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+
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+ ```python
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+ from transformers import AutoTokenizer
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+ from trl import AutoModelForCausalLMWithValueHead
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+
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+ tokenizer = AutoTokenizer.from_pretrained("Evan-Lin//tmp/tmpdxnkhvya/Evan-Lin/Bart-Amazon-rougelastbatch1-attractive2-keywordmax1")
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+ model = AutoModelForCausalLMWithValueHead.from_pretrained("Evan-Lin//tmp/tmpdxnkhvya/Evan-Lin/Bart-Amazon-rougelastbatch1-attractive2-keywordmax1")
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+
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+ inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
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+ outputs = model(**inputs, labels=inputs["input_ids"])
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+ ```
config.json ADDED
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+ {
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+ "_name_or_path": "Evan-Lin/amazon-bart-large-cnn",
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+ "_num_labels": 3,
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+ "activation_dropout": 0.0,
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+ "activation_function": "gelu",
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+ "add_final_layer_norm": false,
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+ "architectures": [
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+ "BartForConditionalGeneration"
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+ ],
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 0,
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+ "classif_dropout": 0.0,
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+ "classifier_dropout": 0.0,
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+ "d_model": 1024,
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+ "decoder_attention_heads": 16,
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+ "decoder_ffn_dim": 4096,
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+ "decoder_layerdrop": 0.0,
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+ "decoder_layers": 12,
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+ "decoder_start_token_id": 2,
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+ "dropout": 0.1,
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+ "early_stopping": true,
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+ "encoder_attention_heads": 16,
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+ "encoder_ffn_dim": 4096,
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+ "encoder_layerdrop": 0.0,
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+ "encoder_layers": 12,
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+ "eos_token_id": 2,
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+ "force_bos_token_to_be_generated": true,
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+ "forced_bos_token_id": 0,
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+ "forced_eos_token_id": 2,
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+ "gradient_checkpointing": false,
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+ "id2label": {
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+ "0": "LABEL_0",
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+ "1": "LABEL_1",
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+ "2": "LABEL_2"
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+ },
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+ "init_std": 0.02,
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+ "is_encoder_decoder": true,
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+ "label2id": {
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+ "LABEL_0": 0,
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+ "LABEL_1": 1,
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+ "LABEL_2": 2
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+ },
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+ "length_penalty": 2.0,
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+ "max_length": 142,
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+ "max_position_embeddings": 1024,
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+ "min_length": 56,
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+ "model_type": "bart",
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+ "no_repeat_ngram_size": 3,
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+ "normalize_before": false,
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+ "num_beams": 4,
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+ "num_hidden_layers": 12,
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+ "output_past": true,
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+ "pad_token_id": 1,
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+ "prefix": " ",
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+ "scale_embedding": false,
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+ "task_specific_params": {
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+ "summarization": {
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+ "early_stopping": true,
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+ "length_penalty": 2.0,
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+ "max_length": 142,
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+ "min_length": 56,
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+ "no_repeat_ngram_size": 3,
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+ "num_beams": 4
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+ }
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+ },
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.29.1",
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+ "use_cache": true,
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+ "vocab_size": 50264
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+ }
generation_config.json ADDED
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+ {
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+ "_from_model_config": true,
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+ "bos_token_id": 0,
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+ "decoder_start_token_id": 2,
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+ "early_stopping": true,
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+ "eos_token_id": 2,
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+ "forced_bos_token_id": 0,
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+ "forced_eos_token_id": 2,
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+ "length_penalty": 2.0,
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+ "max_length": 142,
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+ "min_length": 56,
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+ "no_repeat_ngram_size": 3,
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+ "num_beams": 4,
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+ "pad_token_id": 1,
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+ "transformers_version": "4.29.1"
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+ }
merges.txt ADDED
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pytorch_model.bin ADDED
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special_tokens_map.json ADDED
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+ {
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+ }
tokenizer.json ADDED
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tokenizer_config.json ADDED
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+ {
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+ "add_prefix_space": false,
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+ "bos_token": "<s>",
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+ "clean_up_tokenization_spaces": true,
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+ "cls_token": "<s>",
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+ "eos_token": "</s>",
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+ "errors": "replace",
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+ "mask_token": "<mask>",
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+ "model_max_length": 1024,
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+ "pad_token": "<pad>",
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+ "sep_token": "</s>",
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+ "tokenizer_class": "BartTokenizer",
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+ "trim_offsets": true,
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+ "unk_token": "<unk>"
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+ }
vocab.json ADDED
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