amirabdullah19852020
commited on
Commit
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Push model using huggingface_hub.
Browse files- README.md +42 -0
- config.json +55 -0
- generation_config.json +6 -0
- merges.txt +0 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer_config.json +33 -0
- vocab.json +0 -0
README.md
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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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# TRL Model
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This is a [TRL language model](https://github.com/huggingface/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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## Usage
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To use this model for inference, first install the TRL library:
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```bash
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python -m pip install trl
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```
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You can then generate text as follows:
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```python
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from transformers import pipeline
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generator = pipeline("text-generation", model="amirabdullah19852020//tmp/tmpe3uf80uh/amirabdullah19852020/gpt-neo-125m_utility_reward")
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outputs = generator("Hello, my llama is cute")
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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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```python
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from transformers import AutoTokenizer
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from trl import AutoModelForCausalLMWithValueHead
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tokenizer = AutoTokenizer.from_pretrained("amirabdullah19852020//tmp/tmpe3uf80uh/amirabdullah19852020/gpt-neo-125m_utility_reward")
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model = AutoModelForCausalLMWithValueHead.from_pretrained("amirabdullah19852020//tmp/tmpe3uf80uh/amirabdullah19852020/gpt-neo-125m_utility_reward")
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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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```
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config.json
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{
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"_name_or_path": "EleutherAI/gpt-neo-125m",
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"activation_function": "gelu_new",
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"architectures": [
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"GPTNeoForCausalLM"
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],
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"attention_dropout": 0,
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"attention_layers": [
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"global",
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"local",
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"global",
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"local",
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"global",
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"local",
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"global",
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"local",
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"global",
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"local",
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"global",
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"local"
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],
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"attention_types": [
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[
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[
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"global",
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"local"
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],
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6
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]
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],
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"bos_token_id": 50256,
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"classifier_dropout": 0.1,
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"embed_dropout": 0,
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"eos_token_id": 50256,
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"gradient_checkpointing": false,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": null,
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"layer_norm_epsilon": 1e-05,
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"max_position_embeddings": 2048,
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"model_type": "gpt_neo",
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"num_heads": 12,
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"num_layers": 12,
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"resid_dropout": 0,
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"summary_activation": null,
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"summary_first_dropout": 0.1,
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"summary_proj_to_labels": true,
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"summary_type": "cls_index",
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"summary_use_proj": true,
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"torch_dtype": "float32",
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"transformers_version": "4.32.1",
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"use_cache": true,
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"vocab_size": 50257,
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"window_size": 256
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 50256,
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"eos_token_id": 50256,
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"transformers_version": "4.32.1"
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}
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merges.txt
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:452e39b0916c28da9ff5a05760d4df304a4df71f53cb49cdae9ae33f7e4084c0
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size 500850837
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": "<|endoftext|>",
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"unk_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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tokenizer_config.json
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{
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"add_bos_token": false,
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"add_prefix_space": false,
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"bos_token": {
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"__type": "AddedToken",
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"clean_up_tokenization_spaces": true,
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"eos_token": {
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"__type": "AddedToken",
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"errors": "replace",
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"model_max_length": 2048,
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"pad_token": null,
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"tokenizer_class": "GPT2Tokenizer",
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"unk_token": {
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"__type": "AddedToken",
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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}
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}
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vocab.json
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