Text Generation
Transformers
Safetensors
llama
Generated from Trainer
dpo
trl
conversational
text-generation-inference
Instructions to use BKM1804/ebd3853f-27cd-4553-82ef-b572dab7b9c1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BKM1804/ebd3853f-27cd-4553-82ef-b572dab7b9c1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="BKM1804/ebd3853f-27cd-4553-82ef-b572dab7b9c1") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("BKM1804/ebd3853f-27cd-4553-82ef-b572dab7b9c1") model = AutoModelForCausalLM.from_pretrained("BKM1804/ebd3853f-27cd-4553-82ef-b572dab7b9c1", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use BKM1804/ebd3853f-27cd-4553-82ef-b572dab7b9c1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "BKM1804/ebd3853f-27cd-4553-82ef-b572dab7b9c1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "BKM1804/ebd3853f-27cd-4553-82ef-b572dab7b9c1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/BKM1804/ebd3853f-27cd-4553-82ef-b572dab7b9c1
- SGLang
How to use BKM1804/ebd3853f-27cd-4553-82ef-b572dab7b9c1 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 "BKM1804/ebd3853f-27cd-4553-82ef-b572dab7b9c1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "BKM1804/ebd3853f-27cd-4553-82ef-b572dab7b9c1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "BKM1804/ebd3853f-27cd-4553-82ef-b572dab7b9c1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "BKM1804/ebd3853f-27cd-4553-82ef-b572dab7b9c1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use BKM1804/ebd3853f-27cd-4553-82ef-b572dab7b9c1 with Docker Model Runner:
docker model run hf.co/BKM1804/ebd3853f-27cd-4553-82ef-b572dab7b9c1
Training in progress, step 1000
Browse files- README.md +5 -6
- added_tokens.json +1 -3
- config.json +32 -0
- merges.txt +0 -0
- model.safetensors +3 -0
- special_tokens_map.json +27 -4
- tokenizer.json +2 -2
- tokenizer_config.json +154 -12
- training_args.bin +1 -1
- vocab.json +0 -0
README.md
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---
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base_model: unsloth/
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library_name: transformers
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model_name: ebd3853f-27cd-4553-82ef-b572dab7b9c1
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tags:
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- generated_from_trainer
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- dpo
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- trl
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- unsloth
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licence: license
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---
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# Model Card for ebd3853f-27cd-4553-82ef-b572dab7b9c1
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This model is a fine-tuned version of [unsloth/
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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## Training procedure
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/buikhacminh1804/sn56-dpo-train/runs/
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This model was trained with DPO, a method introduced in [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://huggingface.co/papers/2305.18290).
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### Framework versions
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- TRL: 0.21.0
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- Transformers: 4.55.
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- Pytorch: 2.
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- Datasets: 3.6.0
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- Tokenizers: 0.21.4
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---
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base_model: unsloth/SmolLM2-135M
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library_name: transformers
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model_name: ebd3853f-27cd-4553-82ef-b572dab7b9c1
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tags:
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- generated_from_trainer
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- dpo
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- trl
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licence: license
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---
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# Model Card for ebd3853f-27cd-4553-82ef-b572dab7b9c1
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+
This model is a fine-tuned version of [unsloth/SmolLM2-135M](https://huggingface.co/unsloth/SmolLM2-135M).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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## Training procedure
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/buikhacminh1804/sn56-sft-before-dpo-train/runs/tyf3o6gd)
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This model was trained with DPO, a method introduced in [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://huggingface.co/papers/2305.18290).
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### Framework versions
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- TRL: 0.21.0
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- Transformers: 4.55.2
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- Pytorch: 2.8.0
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- Datasets: 3.6.0
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- Tokenizers: 0.21.4
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added_tokens.json
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{
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"<|
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"<|im_end|>": 151645,
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"<|im_start|>": 151644
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}
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{
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"<|PAD_TOKEN|>": 49152
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}
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config.json
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{
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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": 0,
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"eos_token_id": 0,
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"head_dim": 64,
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"hidden_act": "silu",
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"hidden_size": 576,
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"initializer_range": 0.041666666666666664,
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"intermediate_size": 1536,
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"is_llama_config": true,
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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": 9,
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"num_hidden_layers": 30,
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"num_key_value_heads": 3,
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"pad_token_id": 49152,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_interleaved": false,
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"rope_scaling": null,
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"rope_theta": 100000,
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"tie_word_embeddings": true,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.55.2",
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"use_cache": true,
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"vocab_size": 49153
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}
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merges.txt
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The diff for this file is too large to render.
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5cfa75e60f7b29cf99a9016382a75ec744d038c7b2ca07e627e04a3ea6498199
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size 269061704
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special_tokens_map.json
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{
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"additional_special_tokens": [
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"<|im_start|>",
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"<|im_end|>"
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"eos_token": {
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"content": "<|
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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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"pad_token": {
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"content": "<|
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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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{
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"additional_special_tokens": [
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"<|endoftext|>",
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"<|im_start|>",
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"<|im_end|>",
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"<repo_name>",
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"<reponame>",
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"<file_sep>",
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"<filename>",
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"<gh_stars>",
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"<issue_start>",
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"<issue_comment>",
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"<issue_closed>",
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"<jupyter_start>",
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"<jupyter_text>",
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"<jupyter_code>",
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"<jupyter_output>",
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"<jupyter_script>",
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"<empty_output>"
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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": 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": "<|endoftext|>",
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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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"pad_token": {
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"content": "<|PAD_TOKEN|>",
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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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}
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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-
size
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version https://git-lfs.github.com/spec/v1
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oid sha256:a110eb4e3c8d6a542225a738a2acf1f67b348131d3dd49c926f13223462fff13
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size 3523027
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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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"
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": 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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"content": "<|im_start|>",
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"lstrip": false,
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"normalized": 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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"content": "<|im_end|>",
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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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"additional_special_tokens": [
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"<|im_start|>",
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-
"<|im_end|>"
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],
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-
"bos_token":
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"clean_up_tokenization_spaces": false,
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-
"eos_token": "<|
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-
"errors": "replace",
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"extra_special_tokens": {},
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-
"model_max_length":
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"pad_token": "<|
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"padding_side": "left",
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-
"
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"
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-
"
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}
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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": "<|endoftext|>",
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"lstrip": false,
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"normalized": 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": "<|im_start|>",
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"lstrip": false,
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"normalized": false,
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"single_word": false,
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"special": true
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},
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"2": {
|
| 21 |
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training_args.bin
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|
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size 6993
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vocab.json
CHANGED
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The diff for this file is too large to render.
See raw diff
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