Text Generation
Transformers
Safetensors
llama
trl
dpo
preference-alignment
reasoning
Generated from Trainer
conversational
text-generation-inference
Instructions to use Shekswess/trlm-135m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shekswess/trlm-135m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Shekswess/trlm-135m") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Shekswess/trlm-135m") model = AutoModelForCausalLM.from_pretrained("Shekswess/trlm-135m", 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=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Shekswess/trlm-135m with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Shekswess/trlm-135m" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Shekswess/trlm-135m", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Shekswess/trlm-135m
- SGLang
How to use Shekswess/trlm-135m 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 "Shekswess/trlm-135m" \ --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": "Shekswess/trlm-135m", "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 "Shekswess/trlm-135m" \ --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": "Shekswess/trlm-135m", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Shekswess/trlm-135m with Docker Model Runner:
docker model run hf.co/Shekswess/trlm-135m
Adding ONNX file of this model
#1
by RahulSharma0 - opened
- README.md +1 -0
- onnx/added_tokens.json +4 -0
- onnx/config.json +40 -0
- onnx/generation_config.json +9 -0
- onnx/merges.txt +0 -0
- onnx/model.onnx +3 -0
- onnx/special_tokens_map.json +34 -0
- onnx/tokenizer.json +0 -0
- onnx/tokenizer_config.json +171 -0
- onnx/vocab.json +0 -0
README.md
CHANGED
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@@ -8,6 +8,7 @@ tags:
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- preference-alignment
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- reasoning
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- generated_from_trainer
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model-index:
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- name: trlm-stage-3-dpo-final-2
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results: []
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- preference-alignment
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- reasoning
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- generated_from_trainer
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+
- onnx
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model-index:
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- name: trlm-stage-3-dpo-final-2
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results: []
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onnx/added_tokens.json
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{
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"</think>": 49153,
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"<think>": 49152
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}
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onnx/config.json
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{
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"_attn_implementation_autoset": true,
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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": "bfloat16",
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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": 576,
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"initializer_range": 0.041666666666666664,
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"intermediate_size": 1536,
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| 16 |
+
"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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| 23 |
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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_scaling": null,
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"rope_theta": 100000,
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"tie_word_embeddings": true,
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"torch_dtype": "float32",
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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": "4.51.3",
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"use_cache": true,
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"vocab_size": 49154
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}
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onnx/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": "4.51.3"
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}
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onnx/merges.txt
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onnx/model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:26ffd5753ad86cece13a6a815fe3ddbe1e06c6d36b9b15fbd04f6f31d234a076
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size 652509318
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onnx/special_tokens_map.json
ADDED
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{
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"additional_special_tokens": [
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"<think>",
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"</think>"
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],
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"bos_token": {
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"content": "<|im_start|>",
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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": "<|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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},
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"pad_token": {
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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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},
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"unk_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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}
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onnx/tokenizer.json
ADDED
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onnx/tokenizer_config.json
ADDED
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+
{
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"add_prefix_space": false,
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"added_tokens_decoder": {
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| 4 |
+
"0": {
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| 5 |
+
"content": "<|endoftext|>",
|
| 6 |
+
"lstrip": false,
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| 7 |
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"normalized": false,
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| 8 |
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"rstrip": false,
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| 9 |
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"single_word": false,
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| 10 |
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"special": true
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| 11 |
+
},
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"1": {
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"content": "<|im_start|>",
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"lstrip": false,
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| 15 |
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"normalized": false,
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| 16 |
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"rstrip": false,
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| 17 |
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"single_word": false,
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| 18 |
+
"special": true
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| 19 |
+
},
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| 20 |
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"2": {
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"content": "<|im_end|>",
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| 22 |
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"lstrip": false,
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| 23 |
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"normalized": false,
|
| 24 |
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"rstrip": false,
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| 25 |
+
"single_word": false,
|
| 26 |
+
"special": true
|
| 27 |
+
},
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| 28 |
+
"3": {
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| 29 |
+
"content": "<repo_name>",
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| 30 |
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"lstrip": false,
|
| 31 |
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"normalized": false,
|
| 32 |
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"rstrip": false,
|
| 33 |
+
"single_word": false,
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| 34 |
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"special": true
|
| 35 |
+
},
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| 36 |
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"4": {
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| 37 |
+
"content": "<reponame>",
|
| 38 |
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"lstrip": false,
|
| 39 |
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"normalized": false,
|
| 40 |
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"rstrip": false,
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| 41 |
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"single_word": false,
|
| 42 |
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"special": true
|
| 43 |
+
},
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| 44 |
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"5": {
|
| 45 |
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"content": "<file_sep>",
|
| 46 |
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"lstrip": false,
|
| 47 |
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"normalized": false,
|
| 48 |
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"rstrip": false,
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| 49 |
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"single_word": false,
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| 50 |
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"special": true
|
| 51 |
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},
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| 52 |
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"6": {
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| 53 |
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"content": "<filename>",
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| 54 |
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"lstrip": false,
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| 55 |
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"normalized": false,
|
| 56 |
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| 57 |
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"single_word": false,
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| 58 |
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"special": true
|
| 59 |
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},
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| 60 |
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"7": {
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| 61 |
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"content": "<gh_stars>",
|
| 62 |
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"lstrip": false,
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| 63 |
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"normalized": false,
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| 64 |
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"rstrip": false,
|
| 65 |
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"single_word": false,
|
| 66 |
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"special": true
|
| 67 |
+
},
|
| 68 |
+
"8": {
|
| 69 |
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"content": "<issue_start>",
|
| 70 |
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"lstrip": false,
|
| 71 |
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"normalized": false,
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| 72 |
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"rstrip": false,
|
| 73 |
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"single_word": false,
|
| 74 |
+
"special": true
|
| 75 |
+
},
|
| 76 |
+
"9": {
|
| 77 |
+
"content": "<issue_comment>",
|
| 78 |
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"lstrip": false,
|
| 79 |
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"normalized": false,
|
| 80 |
+
"rstrip": false,
|
| 81 |
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"single_word": false,
|
| 82 |
+
"special": true
|
| 83 |
+
},
|
| 84 |
+
"10": {
|
| 85 |
+
"content": "<issue_closed>",
|
| 86 |
+
"lstrip": false,
|
| 87 |
+
"normalized": false,
|
| 88 |
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"rstrip": false,
|
| 89 |
+
"single_word": false,
|
| 90 |
+
"special": true
|
| 91 |
+
},
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| 92 |
+
"11": {
|
| 93 |
+
"content": "<jupyter_start>",
|
| 94 |
+
"lstrip": false,
|
| 95 |
+
"normalized": false,
|
| 96 |
+
"rstrip": false,
|
| 97 |
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"single_word": false,
|
| 98 |
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"special": true
|
| 99 |
+
},
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| 100 |
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"12": {
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| 101 |
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"content": "<jupyter_text>",
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+
"lstrip": false,
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"normalized": false,
|
| 104 |
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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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+
"13": {
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+
"content": "<jupyter_code>",
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| 110 |
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"lstrip": false,
|
| 111 |
+
"normalized": false,
|
| 112 |
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"rstrip": false,
|
| 113 |
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"single_word": false,
|
| 114 |
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"special": true
|
| 115 |
+
},
|
| 116 |
+
"14": {
|
| 117 |
+
"content": "<jupyter_output>",
|
| 118 |
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"lstrip": false,
|
| 119 |
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"normalized": false,
|
| 120 |
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|
| 121 |
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"single_word": false,
|
| 122 |
+
"special": true
|
| 123 |
+
},
|
| 124 |
+
"15": {
|
| 125 |
+
"content": "<jupyter_script>",
|
| 126 |
+
"lstrip": false,
|
| 127 |
+
"normalized": false,
|
| 128 |
+
"rstrip": false,
|
| 129 |
+
"single_word": false,
|
| 130 |
+
"special": true
|
| 131 |
+
},
|
| 132 |
+
"16": {
|
| 133 |
+
"content": "<empty_output>",
|
| 134 |
+
"lstrip": false,
|
| 135 |
+
"normalized": false,
|
| 136 |
+
"rstrip": false,
|
| 137 |
+
"single_word": false,
|
| 138 |
+
"special": true
|
| 139 |
+
},
|
| 140 |
+
"49152": {
|
| 141 |
+
"content": "<think>",
|
| 142 |
+
"lstrip": false,
|
| 143 |
+
"normalized": false,
|
| 144 |
+
"rstrip": false,
|
| 145 |
+
"single_word": false,
|
| 146 |
+
"special": true
|
| 147 |
+
},
|
| 148 |
+
"49153": {
|
| 149 |
+
"content": "</think>",
|
| 150 |
+
"lstrip": false,
|
| 151 |
+
"normalized": false,
|
| 152 |
+
"rstrip": false,
|
| 153 |
+
"single_word": false,
|
| 154 |
+
"special": true
|
| 155 |
+
}
|
| 156 |
+
},
|
| 157 |
+
"additional_special_tokens": [
|
| 158 |
+
"<think>",
|
| 159 |
+
"</think>"
|
| 160 |
+
],
|
| 161 |
+
"bos_token": "<|im_start|>",
|
| 162 |
+
"chat_template": "{% for message in messages %}\n {% if loop.first and messages[0]['role'] != 'system' %}\n {{ '<|im_start|>system\\nYou are a helpful AI assistant named Tiny Reasoning Language Model, trained by Shekswess. You are an assistant, with the ability to do reasoning. When performing reasoning always perform your full chain of thought inside <think>...</think> before giving a final answer. You are always reasoning so always use <think> </think> tags.<|im_end|>\\n' }}\n {% endif %}\n {{ '<|im_start|>' + message['role'] + '\\n' + message['content'] + '<|im_end|>\\n' }}\n{% endfor %}\n{% if add_generation_prompt %}\n {{ '<|im_start|>assistant\\n' }}\n{% endif %}\n",
|
| 163 |
+
"clean_up_tokenization_spaces": false,
|
| 164 |
+
"eos_token": "<|im_end|>",
|
| 165 |
+
"extra_special_tokens": {},
|
| 166 |
+
"model_max_length": 8192,
|
| 167 |
+
"pad_token": "<|im_end|>",
|
| 168 |
+
"tokenizer_class": "GPT2Tokenizer",
|
| 169 |
+
"unk_token": "<|endoftext|>",
|
| 170 |
+
"vocab_size": 49152
|
| 171 |
+
}
|
onnx/vocab.json
ADDED
|
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