Instructions to use Ba2han/experimental2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ba2han/experimental2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Ba2han/experimental2", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Ba2han/experimental2", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("Ba2han/experimental2", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Ba2han/experimental2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Ba2han/experimental2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Ba2han/experimental2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Ba2han/experimental2
- SGLang
How to use Ba2han/experimental2 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 "Ba2han/experimental2" \ --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": "Ba2han/experimental2", "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 "Ba2han/experimental2" \ --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": "Ba2han/experimental2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Unsloth Studio new
How to use Ba2han/experimental2 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Ba2han/experimental2 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Ba2han/experimental2 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Ba2han/experimental2 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Ba2han/experimental2", max_seq_length=2048, ) - Docker Model Runner
How to use Ba2han/experimental2 with Docker Model Runner:
docker model run hf.co/Ba2han/experimental2
Training in progress, step 300
Browse files- README.md +58 -0
- config.json +90 -0
- generation_config.json +13 -0
- model.safetensors +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +163 -0
- training_args.bin +3 -0
README.md
ADDED
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@@ -0,0 +1,58 @@
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| 1 |
+
---
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| 2 |
+
library_name: transformers
|
| 3 |
+
model_name: experimental2
|
| 4 |
+
tags:
|
| 5 |
+
- generated_from_trainer
|
| 6 |
+
- unsloth
|
| 7 |
+
- trl
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| 8 |
+
- sft
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| 9 |
+
licence: license
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| 10 |
+
---
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| 11 |
+
|
| 12 |
+
# Model Card for experimental2
|
| 13 |
+
|
| 14 |
+
This model is a fine-tuned version of [None](https://huggingface.co/None).
|
| 15 |
+
It has been trained using [TRL](https://github.com/huggingface/trl).
|
| 16 |
+
|
| 17 |
+
## Quick start
|
| 18 |
+
|
| 19 |
+
```python
|
| 20 |
+
from transformers import pipeline
|
| 21 |
+
|
| 22 |
+
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?"
|
| 23 |
+
generator = pipeline("text-generation", model="Ba2han/experimental2", device="cuda")
|
| 24 |
+
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
|
| 25 |
+
print(output["generated_text"])
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| 26 |
+
```
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| 27 |
+
|
| 28 |
+
## Training procedure
|
| 29 |
+
|
| 30 |
+
[<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/batuhan409/huggingface/runs/8fcww366)
|
| 31 |
+
|
| 32 |
+
|
| 33 |
+
This model was trained with SFT.
|
| 34 |
+
|
| 35 |
+
### Framework versions
|
| 36 |
+
|
| 37 |
+
- TRL: 0.24.0
|
| 38 |
+
- Transformers: 5.6.2
|
| 39 |
+
- Pytorch: 2.10.0
|
| 40 |
+
- Datasets: 4.3.0
|
| 41 |
+
- Tokenizers: 0.22.2
|
| 42 |
+
|
| 43 |
+
## Citations
|
| 44 |
+
|
| 45 |
+
|
| 46 |
+
|
| 47 |
+
Cite TRL as:
|
| 48 |
+
|
| 49 |
+
```bibtex
|
| 50 |
+
@misc{vonwerra2022trl,
|
| 51 |
+
title = {{TRL: Transformer Reinforcement Learning}},
|
| 52 |
+
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
|
| 53 |
+
year = 2020,
|
| 54 |
+
journal = {GitHub repository},
|
| 55 |
+
publisher = {GitHub},
|
| 56 |
+
howpublished = {\url{https://github.com/huggingface/trl}}
|
| 57 |
+
}
|
| 58 |
+
```
|
config.json
ADDED
|
@@ -0,0 +1,90 @@
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| 1 |
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{
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| 2 |
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"architectures": [
|
| 3 |
+
"Qwen3CanonForCausalLM"
|
| 4 |
+
],
|
| 5 |
+
"attention_bias": false,
|
| 6 |
+
"attention_dropout": 0.0,
|
| 7 |
+
"auto_map": {
|
| 8 |
+
"AutoModelForCausalLM": "patch.Qwen3CanonForCausalLM"
|
| 9 |
+
},
|
| 10 |
+
"bos_token_id": 50030,
|
| 11 |
+
"dtype": "bfloat16",
|
| 12 |
+
"eos_token_id": 50031,
|
| 13 |
+
"head_dim": 64,
|
| 14 |
+
"hidden_act": "silu",
|
| 15 |
+
"hidden_size": 1024,
|
| 16 |
+
"initializer_range": 0.02,
|
| 17 |
+
"intermediate_size": 4096,
|
| 18 |
+
"layer_types": [
|
| 19 |
+
"full_attention",
|
| 20 |
+
"full_attention",
|
| 21 |
+
"full_attention",
|
| 22 |
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"full_attention",
|
| 23 |
+
"full_attention",
|
| 24 |
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"full_attention",
|
| 25 |
+
"full_attention",
|
| 26 |
+
"full_attention",
|
| 27 |
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"full_attention",
|
| 28 |
+
"full_attention",
|
| 29 |
+
"full_attention",
|
| 30 |
+
"full_attention",
|
| 31 |
+
"full_attention",
|
| 32 |
+
"full_attention",
|
| 33 |
+
"full_attention",
|
| 34 |
+
"full_attention",
|
| 35 |
+
"full_attention",
|
| 36 |
+
"full_attention",
|
| 37 |
+
"full_attention",
|
| 38 |
+
"full_attention",
|
| 39 |
+
"full_attention",
|
| 40 |
+
"full_attention",
|
| 41 |
+
"full_attention",
|
| 42 |
+
"full_attention",
|
| 43 |
+
"full_attention",
|
| 44 |
+
"full_attention",
|
| 45 |
+
"full_attention",
|
| 46 |
+
"full_attention",
|
| 47 |
+
"full_attention",
|
| 48 |
+
"full_attention",
|
| 49 |
+
"full_attention",
|
| 50 |
+
"full_attention",
|
| 51 |
+
"full_attention",
|
| 52 |
+
"full_attention",
|
| 53 |
+
"full_attention",
|
| 54 |
+
"full_attention",
|
| 55 |
+
"full_attention",
|
| 56 |
+
"full_attention",
|
| 57 |
+
"full_attention",
|
| 58 |
+
"full_attention",
|
| 59 |
+
"full_attention",
|
| 60 |
+
"full_attention"
|
| 61 |
+
],
|
| 62 |
+
"max_position_embeddings": 8192,
|
| 63 |
+
"max_window_layers": 42,
|
| 64 |
+
"model_name": "test_checkpoint",
|
| 65 |
+
"model_type": "qwen3",
|
| 66 |
+
"num_attention_heads": 12,
|
| 67 |
+
"num_hidden_layers": 42,
|
| 68 |
+
"num_key_value_heads": 4,
|
| 69 |
+
"pad_token_id": 50034,
|
| 70 |
+
"qk_norm_freeze_affine": true,
|
| 71 |
+
"resid_lambda_init": 1.0,
|
| 72 |
+
"rms_norm_eps": 1e-06,
|
| 73 |
+
"rope_parameters": {
|
| 74 |
+
"rope_theta": 50000,
|
| 75 |
+
"rope_type": "default"
|
| 76 |
+
},
|
| 77 |
+
"sliding_window": null,
|
| 78 |
+
"softcap_divisor": 7.5,
|
| 79 |
+
"softcap_logits": true,
|
| 80 |
+
"softcap_scale": 23.0,
|
| 81 |
+
"softcap_shift": 5.0,
|
| 82 |
+
"tie_word_embeddings": true,
|
| 83 |
+
"transformers_version": "5.6.2",
|
| 84 |
+
"unsloth_version": "2026.4.8",
|
| 85 |
+
"use_cache": false,
|
| 86 |
+
"use_qk_norm_patch": true,
|
| 87 |
+
"use_sliding_window": false,
|
| 88 |
+
"vocab_size": 50048,
|
| 89 |
+
"x0_lambda_init": 0.1
|
| 90 |
+
}
|
generation_config.json
ADDED
|
@@ -0,0 +1,13 @@
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| 1 |
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{
|
| 2 |
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"_from_model_config": true,
|
| 3 |
+
"bos_token_id": 50030,
|
| 4 |
+
"eos_token_id": [
|
| 5 |
+
50031
|
| 6 |
+
],
|
| 7 |
+
"max_length": 8192,
|
| 8 |
+
"output_attentions": false,
|
| 9 |
+
"output_hidden_states": false,
|
| 10 |
+
"pad_token_id": 50034,
|
| 11 |
+
"transformers_version": "5.6.2",
|
| 12 |
+
"use_cache": false
|
| 13 |
+
}
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:bcda3dd42bd162aa2fed5bf0f413cf6ccd8edbd9e8b4685e2589d63f1519595f
|
| 3 |
+
size 1335861472
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
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tokenizer_config.json
ADDED
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| 1 |
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{
|
| 2 |
+
"backend": "tokenizers",
|
| 3 |
+
"bos_token": "<|begin_of_text|>",
|
| 4 |
+
"clean_up_tokenization_spaces": true,
|
| 5 |
+
"eos_token": "<|end_of_text|>",
|
| 6 |
+
"is_local": true,
|
| 7 |
+
"local_files_only": false,
|
| 8 |
+
"model_input_names": [
|
| 9 |
+
"input_ids",
|
| 10 |
+
"attention_mask"
|
| 11 |
+
],
|
| 12 |
+
"model_max_length": 8192,
|
| 13 |
+
"pad_token": "<|finetune_right_pad_id|>",
|
| 14 |
+
"padding_side": "right",
|
| 15 |
+
"tokenizer_class": "TokenizersBackend",
|
| 16 |
+
"unk_token": null,
|
| 17 |
+
"added_tokens_decoder": {
|
| 18 |
+
"50030": {
|
| 19 |
+
"content": "<|begin_of_text|>",
|
| 20 |
+
"single_word": false,
|
| 21 |
+
"lstrip": false,
|
| 22 |
+
"rstrip": false,
|
| 23 |
+
"normalized": false,
|
| 24 |
+
"special": true
|
| 25 |
+
},
|
| 26 |
+
"50031": {
|
| 27 |
+
"content": "<|end_of_text|>",
|
| 28 |
+
"single_word": false,
|
| 29 |
+
"lstrip": false,
|
| 30 |
+
"rstrip": false,
|
| 31 |
+
"normalized": false,
|
| 32 |
+
"special": true
|
| 33 |
+
},
|
| 34 |
+
"50032": {
|
| 35 |
+
"content": "<|reserved_special_token_0|>",
|
| 36 |
+
"single_word": false,
|
| 37 |
+
"lstrip": false,
|
| 38 |
+
"rstrip": false,
|
| 39 |
+
"normalized": false,
|
| 40 |
+
"special": true
|
| 41 |
+
},
|
| 42 |
+
"50033": {
|
| 43 |
+
"content": "<|reserved_special_token_1|>",
|
| 44 |
+
"single_word": false,
|
| 45 |
+
"lstrip": false,
|
| 46 |
+
"rstrip": false,
|
| 47 |
+
"normalized": false,
|
| 48 |
+
"special": true
|
| 49 |
+
},
|
| 50 |
+
"50034": {
|
| 51 |
+
"content": "<|finetune_right_pad_id|>",
|
| 52 |
+
"single_word": false,
|
| 53 |
+
"lstrip": false,
|
| 54 |
+
"rstrip": false,
|
| 55 |
+
"normalized": false,
|
| 56 |
+
"special": true
|
| 57 |
+
},
|
| 58 |
+
"50035": {
|
| 59 |
+
"content": "<|reserved_special_token_2|>",
|
| 60 |
+
"single_word": false,
|
| 61 |
+
"lstrip": false,
|
| 62 |
+
"rstrip": false,
|
| 63 |
+
"normalized": false,
|
| 64 |
+
"special": true
|
| 65 |
+
},
|
| 66 |
+
"50036": {
|
| 67 |
+
"content": "<|start_header_id|>",
|
| 68 |
+
"single_word": false,
|
| 69 |
+
"lstrip": false,
|
| 70 |
+
"rstrip": false,
|
| 71 |
+
"normalized": false,
|
| 72 |
+
"special": true
|
| 73 |
+
},
|
| 74 |
+
"50037": {
|
| 75 |
+
"content": "<|end_header_id|>",
|
| 76 |
+
"single_word": false,
|
| 77 |
+
"lstrip": false,
|
| 78 |
+
"rstrip": false,
|
| 79 |
+
"normalized": false,
|
| 80 |
+
"special": true
|
| 81 |
+
},
|
| 82 |
+
"50038": {
|
| 83 |
+
"content": "<|eom_id|>",
|
| 84 |
+
"single_word": false,
|
| 85 |
+
"lstrip": false,
|
| 86 |
+
"rstrip": false,
|
| 87 |
+
"normalized": false,
|
| 88 |
+
"special": true
|
| 89 |
+
},
|
| 90 |
+
"50039": {
|
| 91 |
+
"content": "<|eot_id|>",
|
| 92 |
+
"single_word": false,
|
| 93 |
+
"lstrip": false,
|
| 94 |
+
"rstrip": false,
|
| 95 |
+
"normalized": false,
|
| 96 |
+
"special": true
|
| 97 |
+
},
|
| 98 |
+
"50040": {
|
| 99 |
+
"content": "<|python_tag|>",
|
| 100 |
+
"single_word": false,
|
| 101 |
+
"lstrip": false,
|
| 102 |
+
"rstrip": false,
|
| 103 |
+
"normalized": false,
|
| 104 |
+
"special": true
|
| 105 |
+
},
|
| 106 |
+
"50041": {
|
| 107 |
+
"content": "<|reserved_special_token_3|>",
|
| 108 |
+
"single_word": false,
|
| 109 |
+
"lstrip": false,
|
| 110 |
+
"rstrip": false,
|
| 111 |
+
"normalized": false,
|
| 112 |
+
"special": true
|
| 113 |
+
},
|
| 114 |
+
"50042": {
|
| 115 |
+
"content": "<|reserved_special_token_4|>",
|
| 116 |
+
"single_word": false,
|
| 117 |
+
"lstrip": false,
|
| 118 |
+
"rstrip": false,
|
| 119 |
+
"normalized": false,
|
| 120 |
+
"special": true
|
| 121 |
+
},
|
| 122 |
+
"50043": {
|
| 123 |
+
"content": "<|reserved_special_token_5|>",
|
| 124 |
+
"single_word": false,
|
| 125 |
+
"lstrip": false,
|
| 126 |
+
"rstrip": false,
|
| 127 |
+
"normalized": false,
|
| 128 |
+
"special": true
|
| 129 |
+
},
|
| 130 |
+
"50044": {
|
| 131 |
+
"content": "<|reserved_special_token_6|>",
|
| 132 |
+
"single_word": false,
|
| 133 |
+
"lstrip": false,
|
| 134 |
+
"rstrip": false,
|
| 135 |
+
"normalized": false,
|
| 136 |
+
"special": true
|
| 137 |
+
},
|
| 138 |
+
"50045": {
|
| 139 |
+
"content": "<|reserved_special_token_7|>",
|
| 140 |
+
"single_word": false,
|
| 141 |
+
"lstrip": false,
|
| 142 |
+
"rstrip": false,
|
| 143 |
+
"normalized": false,
|
| 144 |
+
"special": true
|
| 145 |
+
},
|
| 146 |
+
"50046": {
|
| 147 |
+
"content": "<|reserved_special_token_8|>",
|
| 148 |
+
"single_word": false,
|
| 149 |
+
"lstrip": false,
|
| 150 |
+
"rstrip": false,
|
| 151 |
+
"normalized": false,
|
| 152 |
+
"special": true
|
| 153 |
+
},
|
| 154 |
+
"50047": {
|
| 155 |
+
"content": "<|reserved_special_token_9|>",
|
| 156 |
+
"single_word": false,
|
| 157 |
+
"lstrip": false,
|
| 158 |
+
"rstrip": false,
|
| 159 |
+
"normalized": false,
|
| 160 |
+
"special": true
|
| 161 |
+
}
|
| 162 |
+
}
|
| 163 |
+
}
|
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:71068a80bacd93857bb4df421abb9e81e5fd75c4b132861936dcad82abc86d73
|
| 3 |
+
size 5777
|