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Model: ruslandev/llama-3-8b-gpt-4o-ru1.0 Source: Original Platform
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README.md
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README.md
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---
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license: llama3
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base_model: meta-llama/Meta-Llama-3-8B-Instruct
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tags:
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- generated_from_trainer
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model-index:
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- name: >-
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home/ubuntu/llm_training/axolotl/llama3-8b-gpt-4o-ru/output_llama3_8b_gpt_4o_ru
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results: []
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datasets:
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- ruslandev/tagengo-rus-gpt-4o
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---
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# Llama-3 8B GPT-4o-RU1.0
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[[Dataset]](https://huggingface.co/datasets/ruslandev/tagengo-rus-gpt-4o)
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct).
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The idea behind this model is to train on a dataset derived from a smaller subset of the [tagengo-gpt4](https://huggingface.co/datasets/lightblue/tagengo-gpt4), but with improved data quality.
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I tried to achieve higher data quality by prompting GPT-4o, the latest OpenAI's LLM with better multilingual capabilities. The training objective is primarily focused on the Russian language (80% of the training examples).
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After training for 1 epoch on 2 NVIDIA A100 the model shows promising results on the MT-Bench evaluation benchmark, surpassing GPT-3.5-turbo and being on par with [Suzume](https://huggingface.co/lightblue/suzume-llama-3-8B-multilingual) in Russian language scores,
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even though the latter is trained on 8x bigger and more diverse dataset.
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## How to use
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The easiest way to use this model on your own computer is to use the GGUF version of this model ([ruslandev/llama-3-8b-gpt-4o-ru1.0-gguf](https://huggingface.co/ruslandev/llama-3-8b-gpt-4o-ru1.0-gguf)) using a program such as [llama.cpp](https://github.com/ggerganov/llama.cpp).
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If you want to use this model directly with the Huggingface Transformers stack, I recommend using my framework [gptchain](https://github.com/RuslanPeresy/gptchain).
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```
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git clone https://github.com/RuslanPeresy/gptchain.git
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cd gptchain
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pip install -r requirements-train.txt
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python gptchain.py chat -m ruslandev/llama-3-8b-gpt-4o-ru1.0 \
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--chatml true \
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-q '[{"from": "human", "value": "Из чего состоит нейронная сеть?"}]'
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```
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## Evaluation scores
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I achieved the following scores on Ru/En MT-Bench:
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| |meta-llama/Meta-Llama-3-8B-Instruct | ruslandev/llama-3-8b-gpt-4o-ru1.0 | lightblue/suzume-llama-3-8B-multilingual | Nexusflow/Starling-LM-7B-beta | gpt-3.5-turbo |
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|:----------:|:----------------------------------:|:---------------------------------:|:----------------------------------------:|:-----------------------------:|:-------------:|
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| Russian 🇷🇺 | NaN | 8.12 | 8.19 | 8.06 | 7.94 |
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| English 🇺🇸 | 7.98 | 8.01 | 7.73 | 7.92 | 8.26 |
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## Training procedure
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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<details><summary>See axolotl config</summary>
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axolotl version: `0.4.1`
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```yaml
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base_model: meta-llama/Meta-Llama-3-8B-Instruct
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model_type: LlamaForCausalLM
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tokenizer_type: AutoTokenizer # PreTrainedTokenizerFast
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load_in_8bit: false
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load_in_4bit: false
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strict: false
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datasets:
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- path: ruslandev/tagengo-rus-gpt-4o
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type: sharegpt
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conversation: llama-3
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dataset_prepared_path: /home/ubuntu/llm_training/axolotl/llama3-8b-gpt-4o-ru/prepared_tagengo_rus
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val_set_size: 0.01
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output_dir: /home/ubuntu/llm_training/axolotl/llama3-8b-gpt-4o-ru/output_llama3_8b_gpt_4o_ru
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sequence_len: 8192
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sample_packing: true
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pad_to_sequence_len: true
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eval_sample_packing: false
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use_wandb: false
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#wandb_project: axolotl
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#wandb_entity: wandb_entity
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#wandb_name: llama_3_8b_gpt_4o_ru
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gradient_accumulation_steps: 2
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micro_batch_size: 2
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num_epochs: 1
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optimizer: paged_adamw_8bit
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lr_scheduler: cosine
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learning_rate: 1e-5
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train_on_inputs: false
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group_by_length: false
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bf16: auto
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fp16:
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tf32: false
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gradient_checkpointing: true
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gradient_checkpointing_kwargs:
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use_reentrant: false
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early_stopping_patience:
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resume_from_checkpoint:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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warmup_steps: 10
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evals_per_epoch: 5
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eval_table_size:
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saves_per_epoch: 1
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debug:
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deepspeed: /home/ubuntu/axolotl/deepspeed_configs/zero2.json
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weight_decay: 0.0
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special_tokens:
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pad_token: <|end_of_text|>
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```
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</details><br>
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 2
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 8
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- total_eval_batch_size: 4
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 10
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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 1.1347 | 0.016 | 1 | 1.1086 |
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| 0.916 | 0.208 | 13 | 0.8883 |
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| 0.8494 | 0.416 | 26 | 0.8072 |
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| 0.8657 | 0.624 | 39 | 0.7814 |
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| 0.8077 | 0.832 | 52 | 0.7702 |
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### Framework versions
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- Transformers 4.41.1
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- Pytorch 2.2.2+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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config.json
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{
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"_name_or_path": "meta-llama/Meta-Llama-3-8B-Instruct",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 128000,
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"eos_token_id": 128009,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 8192,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.41.1",
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"use_cache": false,
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"vocab_size": 128256
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}
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"do_sample": true,
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128009
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"max_length": 4096,
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"temperature": 0.6,
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"top_p": 0.9,
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"transformers_version": "4.41.1"
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}
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||||
}
|
||||
3
pytorch_model.bin
Normal file
3
pytorch_model.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
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||||
oid sha256:836b3554c2ee8caabcade24a8d3aab89b9ba0cc92c0300f8fbc702391f56a28c
|
||||
size 16060563132
|
||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|begin_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
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||||
},
|
||||
"eos_token": {
|
||||
"content": "<|eot_id|>",
|
||||
"lstrip": false,
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||||
"normalized": false,
|
||||
"rstrip": false,
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||||
"single_word": false
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||||
},
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||||
"pad_token": {
|
||||
"content": "<|end_of_text|>",
|
||||
"lstrip": false,
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||||
"normalized": false,
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||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
410563
tokenizer.json
Normal file
410563
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
2063
tokenizer_config.json
Normal file
2063
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user