Text Generation
Transformers
Safetensors
llama
Generated from Trainer
trl
hf_jobs
sft
conversational
text-generation-inference
Instructions to use Baon2024/clean with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Baon2024/clean with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Baon2024/clean") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Baon2024/clean") model = AutoModelForCausalLM.from_pretrained("Baon2024/clean", 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 Baon2024/clean with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Baon2024/clean" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Baon2024/clean", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Baon2024/clean
- SGLang
How to use Baon2024/clean 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 "Baon2024/clean" \ --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": "Baon2024/clean", "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 "Baon2024/clean" \ --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": "Baon2024/clean", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Baon2024/clean with Docker Model Runner:
docker model run hf.co/Baon2024/clean
Upload folder using huggingface_hub
Browse files- README.md +58 -0
- chat_template.jinja +6 -0
- checkpoint-10/chat_template.jinja +6 -0
- checkpoint-10/config.json +40 -0
- checkpoint-10/generation_config.json +9 -0
- checkpoint-10/model.safetensors +3 -0
- checkpoint-10/optimizer.pt +3 -0
- checkpoint-10/rng_state.pth +3 -0
- checkpoint-10/scheduler.pt +3 -0
- checkpoint-10/tokenizer.json +0 -0
- checkpoint-10/tokenizer_config.json +17 -0
- checkpoint-10/trainer_state.json +54 -0
- checkpoint-10/training_args.bin +3 -0
- config.json +40 -0
- generation_config.json +9 -0
- model.safetensors +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +17 -0
README.md
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---
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base_model: HuggingFaceTB/SmolLM2-360M-Instruct
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library_name: transformers
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model_name: clean-20260216-172948
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tags:
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- generated_from_trainer
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- trl
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- hf_jobs
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- sft
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licence: license
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---
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# Model Card for clean-20260216-172948
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This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-360M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-360M-Instruct).
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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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```python
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from transformers import pipeline
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question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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generator = pipeline("text-generation", model="None", device="cuda")
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output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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print(output["generated_text"])
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```
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## Training procedure
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This model was trained with SFT.
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### Framework versions
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- TRL: 0.28.0
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- Transformers: 5.1.0
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- Pytorch: 2.10.0
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- Datasets: 4.5.0
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- Tokenizers: 0.22.2
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## Citations
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Cite TRL as:
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```bibtex
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@software{vonwerra2020trl,
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title = {{TRL: Transformers Reinforcement Learning}},
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author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
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license = {Apache-2.0},
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url = {https://github.com/huggingface/trl},
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year = {2020}
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}
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```
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chat_template.jinja
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{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system
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You are a helpful AI assistant named SmolLM, trained by Hugging Face<|im_end|>
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' }}{% endif %}{{'<|im_start|>' + message['role'] + '
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' + message['content'] + '<|im_end|>' + '
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'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
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' }}{% endif %}
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checkpoint-10/chat_template.jinja
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{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system
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You are a helpful AI assistant named SmolLM, trained by Hugging Face<|im_end|>
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' }}{% endif %}{{'<|im_start|>' + message['role'] + '
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' + message['content'] + '<|im_end|>' + '
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'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
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' }}{% endif %}
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checkpoint-10/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": 1,
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"dtype": "float16",
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"eos_token_id": 2,
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"head_dim": 64,
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"hidden_act": "silu",
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"hidden_size": 960,
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"initializer_range": 0.02,
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"intermediate_size": 2560,
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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": 15,
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"num_hidden_layers": 32,
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"num_key_value_heads": 5,
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"pad_token_id": 2,
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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_parameters": {
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"rope_theta": 100000,
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"rope_type": "default"
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},
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"tie_word_embeddings": true,
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"transformers.js_config": {
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"kv_cache_dtype": {
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"fp16": "float16",
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"q4f16": "float16"
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}
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},
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"transformers_version": "5.1.0",
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"use_cache": false,
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"vocab_size": 49152
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}
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checkpoint-10/generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": [
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2
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],
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"pad_token_id": 2,
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"transformers_version": "5.1.0"
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}
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version https://git-lfs.github.com/spec/v1
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oid sha256:ed172e28bef9395097d990c05bb8552667799222410b89c60e516236ef741a61
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size 723674624
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checkpoint-10/optimizer.pt
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version https://git-lfs.github.com/spec/v1
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size 1447529227
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checkpoint-10/rng_state.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:db4b9a24d3e0e9fb6effaa030293ea625c0c78120305ed7a4895568d5b61592b
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size 14645
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checkpoint-10/scheduler.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:3e874b7bd8cf0b0da4cf4a6147ad7fea0c9e6f8b8dc9d57d44d027b9d399f224
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size 1465
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checkpoint-10/tokenizer.json
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The diff for this file is too large to render.
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checkpoint-10/tokenizer_config.json
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{
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"add_prefix_space": false,
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"backend": "tokenizers",
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"bos_token": "<|im_start|>",
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"clean_up_tokenization_spaces": false,
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"eos_token": "<|im_end|>",
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"extra_special_tokens": [
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"<|im_start|>",
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"<|im_end|>"
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],
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"is_local": false,
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"model_max_length": 8192,
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| 13 |
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"pad_token": "<|im_end|>",
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"tokenizer_class": "TokenizersBackend",
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| 15 |
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"unk_token": "<|endoftext|>",
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| 16 |
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"vocab_size": 49152
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| 17 |
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}
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checkpoint-10/trainer_state.json
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{
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"best_global_step": null,
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| 3 |
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"best_metric": null,
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| 4 |
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"best_model_checkpoint": null,
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| 5 |
+
"epoch": 0.5882352941176471,
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| 6 |
+
"eval_steps": 500,
|
| 7 |
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"global_step": 10,
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| 8 |
+
"is_hyper_param_search": false,
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| 9 |
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"is_local_process_zero": true,
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| 10 |
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"is_world_process_zero": true,
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| 11 |
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"log_history": [
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| 12 |
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{
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| 13 |
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"entropy": NaN,
|
| 14 |
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"epoch": 0.29411764705882354,
|
| 15 |
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"grad_norm": NaN,
|
| 16 |
+
"learning_rate": 1.2e-05,
|
| 17 |
+
"loss": 52.629083251953126,
|
| 18 |
+
"mean_token_accuracy": 0.09514285773038864,
|
| 19 |
+
"num_tokens": 1378.0,
|
| 20 |
+
"step": 5
|
| 21 |
+
},
|
| 22 |
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{
|
| 23 |
+
"entropy": NaN,
|
| 24 |
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"epoch": 0.5882352941176471,
|
| 25 |
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"grad_norm": NaN,
|
| 26 |
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"learning_rate": 2.0000000000000003e-06,
|
| 27 |
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"loss": 0.0,
|
| 28 |
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"mean_token_accuracy": 0.0,
|
| 29 |
+
"num_tokens": 2673.0,
|
| 30 |
+
"step": 10
|
| 31 |
+
}
|
| 32 |
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],
|
| 33 |
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"logging_steps": 5,
|
| 34 |
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"max_steps": 10,
|
| 35 |
+
"num_input_tokens_seen": 0,
|
| 36 |
+
"num_train_epochs": 1,
|
| 37 |
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"save_steps": 50,
|
| 38 |
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"stateful_callbacks": {
|
| 39 |
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"TrainerControl": {
|
| 40 |
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"args": {
|
| 41 |
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"should_epoch_stop": false,
|
| 42 |
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"should_evaluate": false,
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| 43 |
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"should_log": false,
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| 44 |
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"should_save": true,
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| 45 |
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"should_training_stop": true
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| 46 |
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},
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| 47 |
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"attributes": {}
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| 48 |
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}
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| 49 |
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},
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| 50 |
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"total_flos": 5046119337600.0,
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| 51 |
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"train_batch_size": 1,
|
| 52 |
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"trial_name": null,
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| 53 |
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"trial_params": null
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| 54 |
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}
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checkpoint-10/training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:5affda892c2be7a7b1bb58363c4ff359ac56a6834514d9728318fb01bb4f8f67
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size 5649
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config.json
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|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"LlamaForCausalLM"
|
| 4 |
+
],
|
| 5 |
+
"attention_bias": false,
|
| 6 |
+
"attention_dropout": 0.0,
|
| 7 |
+
"bos_token_id": 1,
|
| 8 |
+
"dtype": "float16",
|
| 9 |
+
"eos_token_id": 2,
|
| 10 |
+
"head_dim": 64,
|
| 11 |
+
"hidden_act": "silu",
|
| 12 |
+
"hidden_size": 960,
|
| 13 |
+
"initializer_range": 0.02,
|
| 14 |
+
"intermediate_size": 2560,
|
| 15 |
+
"is_llama_config": true,
|
| 16 |
+
"max_position_embeddings": 8192,
|
| 17 |
+
"mlp_bias": false,
|
| 18 |
+
"model_type": "llama",
|
| 19 |
+
"num_attention_heads": 15,
|
| 20 |
+
"num_hidden_layers": 32,
|
| 21 |
+
"num_key_value_heads": 5,
|
| 22 |
+
"pad_token_id": 2,
|
| 23 |
+
"pretraining_tp": 1,
|
| 24 |
+
"rms_norm_eps": 1e-05,
|
| 25 |
+
"rope_interleaved": false,
|
| 26 |
+
"rope_parameters": {
|
| 27 |
+
"rope_theta": 100000,
|
| 28 |
+
"rope_type": "default"
|
| 29 |
+
},
|
| 30 |
+
"tie_word_embeddings": true,
|
| 31 |
+
"transformers.js_config": {
|
| 32 |
+
"kv_cache_dtype": {
|
| 33 |
+
"fp16": "float16",
|
| 34 |
+
"q4f16": "float16"
|
| 35 |
+
}
|
| 36 |
+
},
|
| 37 |
+
"transformers_version": "5.1.0",
|
| 38 |
+
"use_cache": false,
|
| 39 |
+
"vocab_size": 49152
|
| 40 |
+
}
|
generation_config.json
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_from_model_config": true,
|
| 3 |
+
"bos_token_id": 1,
|
| 4 |
+
"eos_token_id": [
|
| 5 |
+
2
|
| 6 |
+
],
|
| 7 |
+
"pad_token_id": 2,
|
| 8 |
+
"transformers_version": "5.1.0"
|
| 9 |
+
}
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ed172e28bef9395097d990c05bb8552667799222410b89c60e516236ef741a61
|
| 3 |
+
size 723674624
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,17 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"backend": "tokenizers",
|
| 4 |
+
"bos_token": "<|im_start|>",
|
| 5 |
+
"clean_up_tokenization_spaces": false,
|
| 6 |
+
"eos_token": "<|im_end|>",
|
| 7 |
+
"extra_special_tokens": [
|
| 8 |
+
"<|im_start|>",
|
| 9 |
+
"<|im_end|>"
|
| 10 |
+
],
|
| 11 |
+
"is_local": false,
|
| 12 |
+
"model_max_length": 8192,
|
| 13 |
+
"pad_token": "<|im_end|>",
|
| 14 |
+
"tokenizer_class": "TokenizersBackend",
|
| 15 |
+
"unk_token": "<|endoftext|>",
|
| 16 |
+
"vocab_size": 49152
|
| 17 |
+
}
|