Upload mean_layernorm_linear_seed6 reward model
Browse files- README.md +28 -0
- checkpoint-4000/config.json +31 -0
- checkpoint-4000/optimizer.pt +3 -0
- checkpoint-4000/pytorch_model.bin +3 -0
- checkpoint-4000/rng_state.pth +3 -0
- checkpoint-4000/scheduler.pt +3 -0
- checkpoint-4000/special_tokens_map.json +14 -0
- checkpoint-4000/tokenizer.json +0 -0
- checkpoint-4000/tokenizer_config.json +9 -0
- checkpoint-4000/trainer_state.json +2591 -0
- checkpoint-4000/training_args.bin +3 -0
- checkpoint-5000/config.json +31 -0
- checkpoint-5000/optimizer.pt +3 -0
- checkpoint-5000/pytorch_model.bin +3 -0
- checkpoint-5000/rng_state.pth +3 -0
- checkpoint-5000/scheduler.pt +3 -0
- checkpoint-5000/special_tokens_map.json +14 -0
- checkpoint-5000/tokenizer.json +0 -0
- checkpoint-5000/tokenizer_config.json +9 -0
- checkpoint-5000/trainer_state.json +3230 -0
- checkpoint-5000/training_args.bin +3 -0
- checkpoint-6000/config.json +31 -0
- checkpoint-6000/optimizer.pt +3 -0
- checkpoint-6000/pytorch_model.bin +3 -0
- checkpoint-6000/rng_state.pth +3 -0
- checkpoint-6000/scheduler.pt +3 -0
- checkpoint-6000/special_tokens_map.json +14 -0
- checkpoint-6000/tokenizer.json +0 -0
- checkpoint-6000/tokenizer_config.json +9 -0
- checkpoint-6000/trainer_state.json +3882 -0
- checkpoint-6000/training_args.bin +3 -0
- checkpoint-7000/config.json +31 -0
- checkpoint-7000/optimizer.pt +3 -0
- checkpoint-7000/pytorch_model.bin +3 -0
- checkpoint-7000/rng_state.pth +3 -0
- checkpoint-7000/scheduler.pt +3 -0
- checkpoint-7000/special_tokens_map.json +14 -0
- checkpoint-7000/tokenizer.json +0 -0
- checkpoint-7000/tokenizer_config.json +9 -0
- checkpoint-7000/trainer_state.json +0 -0
- checkpoint-7000/training_args.bin +3 -0
- config.json +37 -0
- gpt_neox_reward_model.py +188 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +14 -0
- tokenizer.json +0 -0
- tokenizer_config.json +9 -0
- training_args.bin +3 -0
README.md
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---
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library_name: transformers
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tags:
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- reward-model
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- gpt-neox
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- transformers
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---
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# lancehar/mean_layernorm_linear_seed6
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This repository contains the `mean_layernorm_linear_seed6` head-diverse reward model checkpoint from
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`mc-dropout-vs-reward-ensemble`.
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## Loading
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```python
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from transformers import AutoModelForSequenceClassification, AutoTokenizer
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model_name = "lancehar/mean_layernorm_linear_seed6"
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tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
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model = AutoModelForSequenceClassification.from_pretrained(
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model_name,
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trust_remote_code=True,
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)
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```
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These checkpoints use a custom GPT-NeoX reward-model class, so `trust_remote_code=True`
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is required unless you register the class locally from this repository.
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checkpoint-4000/config.json
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{
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"_name_or_path": "tlc4418/pythia_70m_sft",
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"architectures": [
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"GPTNeoXRewardModel"
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],
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"bos_token_id": 0,
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"classifier_dropout": 0.1,
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"eos_token_id": 0,
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"hidden_act": "gelu",
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"hidden_size": 512,
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"initializer_range": 0.02,
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"intermediate_size": 2048,
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 2048,
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"model_type": "gpt_neox_reward_model",
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"num_attention_heads": 8,
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| 17 |
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"num_hidden_layers": 6,
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"pooling": "mean",
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"reward_head_activation": "gelu",
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"reward_head_dropout": 0.0,
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"reward_head_hidden_dim": null,
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"reward_head_type": "layernorm_linear",
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"rotary_emb_base": 10000,
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"rotary_pct": 0.25,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.29.2",
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"use_cache": true,
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"use_parallel_residual": true,
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"vocab_size": 50288
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}
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checkpoint-4000/optimizer.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:06d30e4d56d014d4ac2bba86c71e01ff8493f77e83002e749d7de6834877b055
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size 178704331
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checkpoint-4000/pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:efd31e00d6cef1272ded3193fae34b15e732f44a87e1ba4ea7d927cfd85f5a7c
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size 114527658
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checkpoint-4000/rng_state.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:e57736f8b4fc3a5fc2f8d642816ea7d696c62a173488e45887a3b8588800ba9c
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size 14645
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checkpoint-4000/scheduler.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:04ceebf0b7c7ac22dd16c128651c9f8b29978e2875592278bb5c0914bd31292a
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size 1465
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checkpoint-4000/special_tokens_map.json
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{
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"additional_special_tokens": [
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"<|prefix_end|>",
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"<|assistant|>",
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"<|prefix_begin|>",
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"<|prompter|>",
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"<|system|>"
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],
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"bos_token": "<|endoftext|>",
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"eos_token": "<|endoftext|>",
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"pad_token": "<|padding|>",
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"sep_token": "<|endoftext|>",
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"unk_token": "<|endoftext|>"
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}
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checkpoint-4000/tokenizer.json
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The diff for this file is too large to render.
See raw diff
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checkpoint-4000/tokenizer_config.json
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{
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"add_prefix_space": false,
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"bos_token": "<|endoftext|>",
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"clean_up_tokenization_spaces": true,
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"eos_token": "<|endoftext|>",
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"model_max_length": 1000000000000000019884624838656,
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"tokenizer_class": "GPTNeoXTokenizer",
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"unk_token": "<|endoftext|>"
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}
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checkpoint-4000/trainer_state.json
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oid sha256:15d17db566d266013af03a48da12b993aa2b485f122344645b19641417f7840d
|
| 3 |
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size 4881
|
checkpoint-5000/config.json
ADDED
|
@@ -0,0 +1,31 @@
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|
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|
|
|
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|
|
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|
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|
|
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|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
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|
|
|
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|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_name_or_path": "tlc4418/pythia_70m_sft",
|
| 3 |
+
"architectures": [
|
| 4 |
+
"GPTNeoXRewardModel"
|
| 5 |
+
],
|
| 6 |
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"bos_token_id": 0,
|
| 7 |
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"classifier_dropout": 0.1,
|
| 8 |
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"eos_token_id": 0,
|
| 9 |
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"hidden_act": "gelu",
|
| 10 |
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"hidden_size": 512,
|
| 11 |
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"initializer_range": 0.02,
|
| 12 |
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"intermediate_size": 2048,
|
| 13 |
+
"layer_norm_eps": 1e-05,
|
| 14 |
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"max_position_embeddings": 2048,
|
| 15 |
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"model_type": "gpt_neox_reward_model",
|
| 16 |
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"num_attention_heads": 8,
|
| 17 |
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"num_hidden_layers": 6,
|
| 18 |
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"pooling": "mean",
|
| 19 |
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"reward_head_activation": "gelu",
|
| 20 |
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"reward_head_dropout": 0.0,
|
| 21 |
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"reward_head_hidden_dim": null,
|
| 22 |
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"reward_head_type": "layernorm_linear",
|
| 23 |
+
"rotary_emb_base": 10000,
|
| 24 |
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"rotary_pct": 0.25,
|
| 25 |
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"tie_word_embeddings": false,
|
| 26 |
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"torch_dtype": "bfloat16",
|
| 27 |
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"transformers_version": "4.29.2",
|
| 28 |
+
"use_cache": true,
|
| 29 |
+
"use_parallel_residual": true,
|
| 30 |
+
"vocab_size": 50288
|
| 31 |
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}
|
checkpoint-5000/optimizer.pt
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
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version https://git-lfs.github.com/spec/v1
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| 3 |
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size 178704331
|
checkpoint-5000/pytorch_model.bin
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
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version https://git-lfs.github.com/spec/v1
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oid sha256:1e4b8390998307d7f76ad40137359d8ccd2bddcf8900c768fdfe9cc94ed6c453
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| 3 |
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size 114527658
|
checkpoint-5000/rng_state.pth
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
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version https://git-lfs.github.com/spec/v1
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| 3 |
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size 14645
|
checkpoint-5000/scheduler.pt
ADDED
|
@@ -0,0 +1,3 @@
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|
|
|
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| 1 |
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version https://git-lfs.github.com/spec/v1
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oid sha256:ad5809b1125a8b8d59bbfd55f25693fa27f204ad97152b395aac8149077ddd68
|
| 3 |
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size 1465
|
checkpoint-5000/special_tokens_map.json
ADDED
|
@@ -0,0 +1,14 @@
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|
| 1 |
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{
|
| 2 |
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"additional_special_tokens": [
|
| 3 |
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"<|prefix_end|>",
|
| 4 |
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"<|assistant|>",
|
| 5 |
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"<|prefix_begin|>",
|
| 6 |
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"<|prompter|>",
|
| 7 |
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"<|system|>"
|
| 8 |
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],
|
| 9 |
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"bos_token": "<|endoftext|>",
|
| 10 |
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"eos_token": "<|endoftext|>",
|
| 11 |
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"pad_token": "<|padding|>",
|
| 12 |
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"sep_token": "<|endoftext|>",
|
| 13 |
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"unk_token": "<|endoftext|>"
|
| 14 |
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}
|
checkpoint-5000/tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
checkpoint-5000/tokenizer_config.json
ADDED
|
@@ -0,0 +1,9 @@
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| 1 |
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{
|
| 2 |
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"add_prefix_space": false,
|
| 3 |
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"bos_token": "<|endoftext|>",
|
| 4 |
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"clean_up_tokenization_spaces": true,
|
| 5 |
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"eos_token": "<|endoftext|>",
|
| 6 |
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"model_max_length": 1000000000000000019884624838656,
|
| 7 |
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"tokenizer_class": "GPTNeoXTokenizer",
|
| 8 |
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"unk_token": "<|endoftext|>"
|
| 9 |
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}
|
checkpoint-5000/trainer_state.json
ADDED
|
@@ -0,0 +1,3230 @@
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|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"additional_special_tokens": [
|
| 3 |
+
"<|prefix_end|>",
|
| 4 |
+
"<|assistant|>",
|
| 5 |
+
"<|prefix_begin|>",
|
| 6 |
+
"<|prompter|>",
|
| 7 |
+
"<|system|>"
|
| 8 |
+
],
|
| 9 |
+
"bos_token": "<|endoftext|>",
|
| 10 |
+
"eos_token": "<|endoftext|>",
|
| 11 |
+
"pad_token": "<|padding|>",
|
| 12 |
+
"sep_token": "<|endoftext|>",
|
| 13 |
+
"unk_token": "<|endoftext|>"
|
| 14 |
+
}
|
checkpoint-7000/tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
checkpoint-7000/tokenizer_config.json
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"bos_token": "<|endoftext|>",
|
| 4 |
+
"clean_up_tokenization_spaces": true,
|
| 5 |
+
"eos_token": "<|endoftext|>",
|
| 6 |
+
"model_max_length": 1000000000000000019884624838656,
|
| 7 |
+
"tokenizer_class": "GPTNeoXTokenizer",
|
| 8 |
+
"unk_token": "<|endoftext|>"
|
| 9 |
+
}
|
checkpoint-7000/trainer_state.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
checkpoint-7000/training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:15d17db566d266013af03a48da12b993aa2b485f122344645b19641417f7840d
|
| 3 |
+
size 4881
|
config.json
ADDED
|
@@ -0,0 +1,37 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_name_or_path": "tlc4418/pythia_70m_sft",
|
| 3 |
+
"architectures": [
|
| 4 |
+
"GPTNeoXRewardModel"
|
| 5 |
+
],
|
| 6 |
+
"bos_token_id": 0,
|
| 7 |
+
"classifier_dropout": 0.1,
|
| 8 |
+
"eos_token_id": 0,
|
| 9 |
+
"hidden_act": "gelu",
|
| 10 |
+
"hidden_size": 512,
|
| 11 |
+
"initializer_range": 0.02,
|
| 12 |
+
"intermediate_size": 2048,
|
| 13 |
+
"layer_norm_eps": 1e-05,
|
| 14 |
+
"max_position_embeddings": 2048,
|
| 15 |
+
"mean": -0.1044921875,
|
| 16 |
+
"model_type": "gpt_neox_reward_model",
|
| 17 |
+
"num_attention_heads": 8,
|
| 18 |
+
"num_hidden_layers": 6,
|
| 19 |
+
"pooling": "mean",
|
| 20 |
+
"reward_head_activation": "gelu",
|
| 21 |
+
"reward_head_dropout": 0.0,
|
| 22 |
+
"reward_head_hidden_dim": null,
|
| 23 |
+
"reward_head_type": "layernorm_linear",
|
| 24 |
+
"rotary_emb_base": 10000,
|
| 25 |
+
"rotary_pct": 0.25,
|
| 26 |
+
"std": 1.1328125,
|
| 27 |
+
"tie_word_embeddings": false,
|
| 28 |
+
"torch_dtype": "bfloat16",
|
| 29 |
+
"transformers_version": "4.29.2",
|
| 30 |
+
"use_cache": true,
|
| 31 |
+
"use_parallel_residual": true,
|
| 32 |
+
"vocab_size": 50288,
|
| 33 |
+
"auto_map": {
|
| 34 |
+
"AutoConfig": "gpt_neox_reward_model.GPTNeoXRewardModelConfig",
|
| 35 |
+
"AutoModelForSequenceClassification": "gpt_neox_reward_model.GPTNeoXRewardModel"
|
| 36 |
+
}
|
| 37 |
+
}
|
gpt_neox_reward_model.py
ADDED
|
@@ -0,0 +1,188 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
from dataclasses import dataclass
|
| 2 |
+
from typing import Literal, Optional
|
| 3 |
+
|
| 4 |
+
import torch
|
| 5 |
+
import torch.nn as nn
|
| 6 |
+
from transformers import AutoConfig, AutoModelForSequenceClassification
|
| 7 |
+
from transformers.models.gpt_neox.modeling_gpt_neox import GPTNeoXConfig, GPTNeoXModel, GPTNeoXPreTrainedModel
|
| 8 |
+
from transformers.utils import ModelOutput
|
| 9 |
+
|
| 10 |
+
|
| 11 |
+
def _get_activation(name: str) -> nn.Module:
|
| 12 |
+
activations = {
|
| 13 |
+
"gelu": nn.GELU,
|
| 14 |
+
"relu": nn.ReLU,
|
| 15 |
+
"silu": nn.SiLU,
|
| 16 |
+
"tanh": nn.Tanh,
|
| 17 |
+
}
|
| 18 |
+
if name not in activations:
|
| 19 |
+
raise ValueError(f"Unsupported reward-head activation: {name}")
|
| 20 |
+
return activations[name]()
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
class LayerNormLinearRewardHead(nn.Module):
|
| 24 |
+
def __init__(self, hidden_size: int):
|
| 25 |
+
super().__init__()
|
| 26 |
+
self.norm = nn.LayerNorm(hidden_size)
|
| 27 |
+
self.proj = nn.Linear(hidden_size, 1)
|
| 28 |
+
|
| 29 |
+
def forward(self, pooled: torch.FloatTensor) -> torch.FloatTensor:
|
| 30 |
+
return self.proj(self.norm(pooled))
|
| 31 |
+
|
| 32 |
+
|
| 33 |
+
class MLPRewardHead(nn.Module):
|
| 34 |
+
def __init__(self, hidden_size: int, hidden_dim: int, dropout: float, activation: str):
|
| 35 |
+
super().__init__()
|
| 36 |
+
self.net = nn.Sequential(
|
| 37 |
+
nn.LayerNorm(hidden_size),
|
| 38 |
+
nn.Linear(hidden_size, hidden_dim),
|
| 39 |
+
_get_activation(activation),
|
| 40 |
+
nn.Dropout(dropout),
|
| 41 |
+
nn.Linear(hidden_dim, 1),
|
| 42 |
+
)
|
| 43 |
+
|
| 44 |
+
def forward(self, pooled: torch.FloatTensor) -> torch.FloatTensor:
|
| 45 |
+
return self.net(pooled)
|
| 46 |
+
|
| 47 |
+
|
| 48 |
+
class GatedMLPRewardHead(nn.Module):
|
| 49 |
+
def __init__(self, hidden_size: int, hidden_dim: int, dropout: float):
|
| 50 |
+
super().__init__()
|
| 51 |
+
self.norm = nn.LayerNorm(hidden_size)
|
| 52 |
+
self.value_proj = nn.Linear(hidden_size, hidden_dim)
|
| 53 |
+
self.gate_proj = nn.Linear(hidden_size, hidden_dim)
|
| 54 |
+
self.dropout = nn.Dropout(dropout)
|
| 55 |
+
self.out_proj = nn.Linear(hidden_dim, 1)
|
| 56 |
+
|
| 57 |
+
def forward(self, pooled: torch.FloatTensor) -> torch.FloatTensor:
|
| 58 |
+
pooled = self.norm(pooled)
|
| 59 |
+
hidden = self.value_proj(pooled) * torch.sigmoid(self.gate_proj(pooled))
|
| 60 |
+
hidden = self.dropout(hidden)
|
| 61 |
+
return self.out_proj(hidden)
|
| 62 |
+
|
| 63 |
+
|
| 64 |
+
def build_reward_head(
|
| 65 |
+
hidden_size: int,
|
| 66 |
+
head_type: str,
|
| 67 |
+
hidden_dim: Optional[int],
|
| 68 |
+
dropout: float,
|
| 69 |
+
activation: str,
|
| 70 |
+
) -> nn.Module:
|
| 71 |
+
resolved_hidden_dim = hidden_dim or hidden_size
|
| 72 |
+
|
| 73 |
+
if head_type == "linear":
|
| 74 |
+
return nn.Linear(hidden_size, 1)
|
| 75 |
+
if head_type == "layernorm_linear":
|
| 76 |
+
return LayerNormLinearRewardHead(hidden_size)
|
| 77 |
+
if head_type == "mlp":
|
| 78 |
+
return MLPRewardHead(hidden_size, resolved_hidden_dim, dropout, activation)
|
| 79 |
+
if head_type == "gated_mlp":
|
| 80 |
+
return GatedMLPRewardHead(hidden_size, resolved_hidden_dim, dropout)
|
| 81 |
+
raise ValueError(f"Unsupported reward head type: {head_type}")
|
| 82 |
+
|
| 83 |
+
|
| 84 |
+
class GPTNeoXRewardModelConfig(GPTNeoXConfig):
|
| 85 |
+
model_type = "gpt_neox_reward_model"
|
| 86 |
+
|
| 87 |
+
pooling: Literal["mean", "last"]
|
| 88 |
+
reward_head_type: Literal["linear", "layernorm_linear", "mlp", "gated_mlp"]
|
| 89 |
+
reward_head_hidden_dim: Optional[int]
|
| 90 |
+
reward_head_dropout: float
|
| 91 |
+
reward_head_activation: Literal["gelu", "relu", "silu", "tanh"]
|
| 92 |
+
|
| 93 |
+
def __init__(
|
| 94 |
+
self,
|
| 95 |
+
pooling: Literal["mean", "last"] = "last",
|
| 96 |
+
reward_head_type: Literal["linear", "layernorm_linear", "mlp", "gated_mlp"] = "linear",
|
| 97 |
+
reward_head_hidden_dim: Optional[int] = None,
|
| 98 |
+
reward_head_dropout: float = 0.0,
|
| 99 |
+
reward_head_activation: Literal["gelu", "relu", "silu", "tanh"] = "gelu",
|
| 100 |
+
**kwargs,
|
| 101 |
+
):
|
| 102 |
+
super().__init__(**kwargs)
|
| 103 |
+
self.pooling = pooling or "last"
|
| 104 |
+
self.reward_head_type = reward_head_type or "linear"
|
| 105 |
+
self.reward_head_hidden_dim = reward_head_hidden_dim
|
| 106 |
+
self.reward_head_dropout = reward_head_dropout
|
| 107 |
+
self.reward_head_activation = reward_head_activation or "gelu"
|
| 108 |
+
|
| 109 |
+
|
| 110 |
+
@dataclass
|
| 111 |
+
class GPTNeoXRewardModelOutput(ModelOutput):
|
| 112 |
+
logits: torch.FloatTensor = None
|
| 113 |
+
|
| 114 |
+
|
| 115 |
+
class GPTNeoXRewardModel(GPTNeoXPreTrainedModel):
|
| 116 |
+
config_class = GPTNeoXRewardModelConfig
|
| 117 |
+
|
| 118 |
+
def __init__(self, config):
|
| 119 |
+
if type(config) == GPTNeoXConfig:
|
| 120 |
+
# Preserve the upstream behavior where a base GPT-NeoX config can
|
| 121 |
+
# be promoted into the reward-model config during loading.
|
| 122 |
+
config = GPTNeoXRewardModelConfig.from_dict(config.to_dict())
|
| 123 |
+
super().__init__(config)
|
| 124 |
+
|
| 125 |
+
self.gpt_neox = GPTNeoXModel(config)
|
| 126 |
+
# Keep the reward head declared locally so it can be modified here
|
| 127 |
+
# without relying on the packaged `model_training` implementation.
|
| 128 |
+
self.out_proj = build_reward_head(
|
| 129 |
+
hidden_size=config.hidden_size,
|
| 130 |
+
head_type=getattr(config, "reward_head_type", "linear"),
|
| 131 |
+
hidden_dim=getattr(config, "reward_head_hidden_dim", None),
|
| 132 |
+
dropout=getattr(config, "reward_head_dropout", 0.0),
|
| 133 |
+
activation=getattr(config, "reward_head_activation", "gelu"),
|
| 134 |
+
)
|
| 135 |
+
self.pooling = config.pooling
|
| 136 |
+
self.post_init()
|
| 137 |
+
|
| 138 |
+
@property
|
| 139 |
+
def reward_head(self) -> nn.Module:
|
| 140 |
+
return self.out_proj
|
| 141 |
+
|
| 142 |
+
def forward(
|
| 143 |
+
self,
|
| 144 |
+
input_ids,
|
| 145 |
+
attention_mask: Optional[torch.FloatTensor] = None,
|
| 146 |
+
inputs_embeds: Optional[torch.FloatTensor] = None,
|
| 147 |
+
head_mask: Optional[torch.FloatTensor] = None,
|
| 148 |
+
use_cache: Optional[bool] = None,
|
| 149 |
+
return_dict: Optional[bool] = True,
|
| 150 |
+
) -> GPTNeoXRewardModelOutput:
|
| 151 |
+
outputs = self.gpt_neox(
|
| 152 |
+
input_ids,
|
| 153 |
+
attention_mask=attention_mask,
|
| 154 |
+
head_mask=head_mask,
|
| 155 |
+
inputs_embeds=inputs_embeds,
|
| 156 |
+
use_cache=use_cache,
|
| 157 |
+
return_dict=return_dict,
|
| 158 |
+
)
|
| 159 |
+
|
| 160 |
+
hidden_states = outputs[0]
|
| 161 |
+
if self.pooling == "mean":
|
| 162 |
+
if attention_mask is None:
|
| 163 |
+
pooled = hidden_states.mean(dim=1)
|
| 164 |
+
else:
|
| 165 |
+
mask = attention_mask.to(hidden_states.dtype).unsqueeze(-1)
|
| 166 |
+
pooled = (hidden_states * mask).sum(dim=1) / mask.sum(dim=1).clamp_min(1.0)
|
| 167 |
+
elif self.pooling == "last":
|
| 168 |
+
if attention_mask is None:
|
| 169 |
+
pooled = hidden_states[:, -1]
|
| 170 |
+
else:
|
| 171 |
+
last_idx = attention_mask.long().sum(dim=1).clamp_min(1) - 1
|
| 172 |
+
pooled = hidden_states.gather(
|
| 173 |
+
1,
|
| 174 |
+
last_idx.view(-1, 1, 1).expand(-1, 1, hidden_states.size(-1)),
|
| 175 |
+
).squeeze(1)
|
| 176 |
+
else:
|
| 177 |
+
raise ValueError(f"Unknown pooling method: {self.pooling}")
|
| 178 |
+
|
| 179 |
+
logits = self.out_proj(pooled)
|
| 180 |
+
|
| 181 |
+
if not return_dict:
|
| 182 |
+
return (logits,) + outputs[1:]
|
| 183 |
+
|
| 184 |
+
return GPTNeoXRewardModelOutput(logits=logits)
|
| 185 |
+
|
| 186 |
+
|
| 187 |
+
AutoConfig.register("gpt_neox_reward_model", GPTNeoXRewardModelConfig)
|
| 188 |
+
AutoModelForSequenceClassification.register(GPTNeoXRewardModelConfig, GPTNeoXRewardModel)
|
pytorch_model.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f5277f93106c5f7312d2d9fe666702cc1b43a6de7f74bcfcbdfafe66eef0a8f6
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| 3 |
+
size 114527658
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,14 @@
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|
| 1 |
+
{
|
| 2 |
+
"additional_special_tokens": [
|
| 3 |
+
"<|prefix_end|>",
|
| 4 |
+
"<|assistant|>",
|
| 5 |
+
"<|prefix_begin|>",
|
| 6 |
+
"<|prompter|>",
|
| 7 |
+
"<|system|>"
|
| 8 |
+
],
|
| 9 |
+
"bos_token": "<|endoftext|>",
|
| 10 |
+
"eos_token": "<|endoftext|>",
|
| 11 |
+
"pad_token": "<|padding|>",
|
| 12 |
+
"sep_token": "<|endoftext|>",
|
| 13 |
+
"unk_token": "<|endoftext|>"
|
| 14 |
+
}
|
tokenizer.json
ADDED
|
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tokenizer_config.json
ADDED
|
@@ -0,0 +1,9 @@
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|
|
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|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"bos_token": "<|endoftext|>",
|
| 4 |
+
"clean_up_tokenization_spaces": true,
|
| 5 |
+
"eos_token": "<|endoftext|>",
|
| 6 |
+
"model_max_length": 1000000000000000019884624838656,
|
| 7 |
+
"tokenizer_class": "GPTNeoXTokenizer",
|
| 8 |
+
"unk_token": "<|endoftext|>"
|
| 9 |
+
}
|
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
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|
|
|
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|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:15d17db566d266013af03a48da12b993aa2b485f122344645b19641417f7840d
|
| 3 |
+
size 4881
|