Instructions to use realsanjeev/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use realsanjeev/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="realsanjeev/results")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("realsanjeev/results") model = AutoModelForSeq2SeqLM.from_pretrained("realsanjeev/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use realsanjeev/results with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "realsanjeev/results" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "realsanjeev/results", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/realsanjeev/results
- SGLang
How to use realsanjeev/results with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "realsanjeev/results" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "realsanjeev/results", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "realsanjeev/results" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "realsanjeev/results", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use realsanjeev/results with Docker Model Runner:
docker model run hf.co/realsanjeev/results
Sanjeev Bhandari commited on
Training in progress, step 500
Browse files- added_tokens.json +4 -0
- config.json +50 -0
- model.safetensors +3 -0
- special_tokens_map.json +51 -0
- tokenizer.json +0 -0
- tokenizer_config.json +80 -0
- training_args.bin +3 -0
- unigram.json +0 -0
added_tokens.json
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{
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"</s>": 55000,
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"<s>": 55001
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}
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config.json
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{
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"_name_or_path": "sanjeev-bhandari01/nepali-text-summerization",
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"activation_dropout": 0.0,
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"activation_function": "gelu",
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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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"classifier_dropout": 0.0,
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"d_model": 768,
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"decoder_attention_heads": 6,
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"decoder_ffn_dim": 768,
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"decoder_layerdrop": 0.0,
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"decoder_layers": 6,
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"decoder_start_token_id": 1,
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"do_sample": true,
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"dropout": 0.1,
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"encoder_attention_heads": 6,
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"encoder_ffn_dim": 768,
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"encoder_layerdrop": 0.0,
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"encoder_layers": 6,
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"eos_token_id": 1,
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"forced_eos_token_id": 1,
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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": 128,
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"max_position_embeddings": 1000,
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"min_length": 32,
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"model_type": "bart",
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"num_beams": 4,
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"num_hidden_layers": 6,
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"pad_token_id": 3,
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"scale_embedding": false,
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"torch_dtype": "float32",
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"transformers_version": "4.35.2",
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"use_cache": true,
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"vocab_size": 55000
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5e612e9c620d09618dc1f3451c4a019534d004cb625536660ac9c962e17e4831
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size 402350000
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<cls>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"cls_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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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": "<sep>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"mask_token": {
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"content": "<mask>",
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"lstrip": true,
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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": {
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"content": "<pad>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"sep_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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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_prefix_space": false,
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"added_tokens_decoder": {
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"0": {
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"content": "<cls>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"1": {
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"content": "<sep>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"2": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"3": {
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"content": "<pad>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"4": {
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"content": "<mask>",
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"lstrip": true,
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"normalized": true,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"55000": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"55001": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"bos_token": "<cls>",
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"clean_up_tokenization_spaces": true,
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"cls_token": "<s>",
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"eos_token": "<sep>",
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"errors": "replace",
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"mask_token": "<mask>",
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"max_length": 1000,
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"model_max_length": 1000,
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"pad_to_multiple_of": null,
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"pad_token": "<pad>",
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"pad_token_type_id": 0,
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"padding_side": "right",
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"sep_token": "</s>",
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"stride": 0,
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"tokenizer_class": "BartTokenizer",
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"trim_offsets": true,
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"truncation_side": "right",
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"truncation_strategy": "longest_first",
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"unk_token": "<unk>"
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}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:8e3590036515e42deb93fa456c7e33d0b0dc7e3b50de1abe79bb66b7a80c182b
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size 4664
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unigram.json
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