Text Generation
PEFT
Safetensors
Transformers
qwen2
lora
sft
trl
conversational
text-generation-inference
Instructions to use Vigp17/agentcode-14b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Vigp17/agentcode-14b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Coder-14B-Instruct") model = PeftModel.from_pretrained(base_model, "Vigp17/agentcode-14b") - Transformers
How to use Vigp17/agentcode-14b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Vigp17/agentcode-14b") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("Vigp17/agentcode-14b") model = AutoModelForMultimodalLM.from_pretrained("Vigp17/agentcode-14b") 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 Vigp17/agentcode-14b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Vigp17/agentcode-14b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Vigp17/agentcode-14b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Vigp17/agentcode-14b
- SGLang
How to use Vigp17/agentcode-14b 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 "Vigp17/agentcode-14b" \ --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": "Vigp17/agentcode-14b", "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 "Vigp17/agentcode-14b" \ --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": "Vigp17/agentcode-14b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Vigp17/agentcode-14b with Docker Model Runner:
docker model run hf.co/Vigp17/agentcode-14b
Trained adapter v1 (xLAM + synthetic, completion-only)
Browse files- README.md +14 -4
- adapter_config.json +48 -0
- adapter_model.safetensors +3 -0
- added_tokens.json +24 -0
- merges.txt +0 -0
- optimizer.pt +3 -0
- rng_state.pth +3 -0
- scheduler.pt +3 -0
- special_tokens_map.json +31 -0
- tokenizer.json +2 -2
- tokenizer_config.json +185 -7
- trainer_state.json +189 -0
- training_args.bin +3 -0
- vocab.json +0 -0
README.md
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---
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# Model Card for Model ID
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<!-- Provide a longer summary of what this model is. -->
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-
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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## Model Card Contact
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[More Information Needed]
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---
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base_model: Qwen/Qwen2.5-Coder-14B-Instruct
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library_name: peft
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pipeline_tag: text-generation
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tags:
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- base_model:adapter:Qwen/Qwen2.5-Coder-14B-Instruct
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- lora
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- sft
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- transformers
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- trl
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---
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# Model Card for Model ID
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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## Model Card Contact
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[More Information Needed]
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### Framework versions
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- PEFT 0.19.1
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adapter_config.json
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{
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"alora_invocation_tokens": null,
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"alpha_pattern": {},
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"arrow_config": null,
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"auto_mapping": null,
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"base_model_name_or_path": "Qwen/Qwen2.5-Coder-14B-Instruct",
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"bias": "none",
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"corda_config": null,
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"ensure_weight_tying": false,
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"eva_config": null,
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"exclude_modules": null,
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 32,
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"lora_bias": false,
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"lora_dropout": 0.05,
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"lora_ga_config": null,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"peft_version": "0.19.1",
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"qalora_group_size": 16,
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"gate_proj",
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"up_proj",
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"k_proj",
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"down_proj",
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"o_proj",
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"q_proj"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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"trainable_token_indices": null,
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"use_bdlora": null,
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"use_dora": false,
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"use_qalora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:6c7c4239ee188cca5be79f702485a937eaa89a07f024232a5d04f39a24c8f3a7
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size 275341720
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added_tokens.json
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{
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"<|endoftext|>": 151643,
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"<|vision_pad|>": 151654,
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"<|vision_start|>": 151652
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}
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merges.txt
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optimizer.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:a66633aa287f3cd50de2e3a4ab29c34ac32734d07da56ed4e4d4948622f34d37
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size 551070514
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rng_state.pth
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size 14244
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scheduler.pt
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size 1064
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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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"<|object_ref_start|>",
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"<|object_ref_end|>",
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"<|box_end|>",
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"<|quad_start|>",
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"<|quad_end|>",
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"<|vision_start|>",
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"<|vision_end|>",
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"<|vision_pad|>",
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"<|image_pad|>",
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"<|video_pad|>"
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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": "<|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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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 sha256:913950e4971737031da511cdd1b410daae4566f62eb845b3975bca5a102323d8
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size 11421995
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tokenizer_config.json
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{
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"model_max_length": 32768,
|
| 25 |
"pad_token": "<|endoftext|>",
|
| 26 |
"split_special_tokens": false,
|
|
|
|
| 1 |
{
|
| 2 |
+
"add_bos_token": false,
|
| 3 |
"add_prefix_space": false,
|
| 4 |
+
"added_tokens_decoder": {
|
| 5 |
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"151643": {
|
| 6 |
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"content": "<|endoftext|>",
|
| 7 |
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"lstrip": false,
|
| 8 |
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"normalized": false,
|
| 9 |
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"rstrip": false,
|
| 10 |
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"single_word": false,
|
| 11 |
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"special": true
|
| 12 |
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},
|
| 13 |
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"151644": {
|
| 14 |
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"content": "<|im_start|>",
|
| 15 |
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"lstrip": false,
|
| 16 |
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"normalized": false,
|
| 17 |
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"rstrip": false,
|
| 18 |
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"single_word": false,
|
| 19 |
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"special": true
|
| 20 |
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},
|
| 21 |
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"151645": {
|
| 22 |
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"content": "<|im_end|>",
|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
| 27 |
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"special": true
|
| 28 |
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|
| 29 |
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"151646": {
|
| 30 |
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"content": "<|object_ref_start|>",
|
| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
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|
| 35 |
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|
| 36 |
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|
| 37 |
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"151647": {
|
| 38 |
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"content": "<|object_ref_end|>",
|
| 39 |
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|
| 40 |
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|
| 41 |
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|
| 42 |
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|
| 43 |
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|
| 44 |
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| 45 |
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|
| 46 |
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| 47 |
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| 48 |
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| 49 |
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| 50 |
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| 51 |
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|
| 52 |
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| 53 |
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|
| 54 |
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| 55 |
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| 56 |
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| 57 |
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| 58 |
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| 59 |
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| 60 |
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| 61 |
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| 62 |
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|
| 63 |
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| 64 |
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| 65 |
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| 67 |
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| 68 |
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| 69 |
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"151651": {
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| 70 |
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|
| 71 |
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|
| 72 |
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| 73 |
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|
| 74 |
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| 75 |
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| 76 |
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| 77 |
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|
| 78 |
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|
| 79 |
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| 80 |
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| 81 |
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| 83 |
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| 84 |
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| 86 |
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|
| 87 |
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| 88 |
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| 89 |
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|
| 90 |
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|
| 91 |
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| 92 |
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| 93 |
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|
| 94 |
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| 95 |
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| 96 |
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| 97 |
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|
| 98 |
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|
| 99 |
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| 100 |
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| 101 |
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|
| 102 |
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| 103 |
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| 104 |
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| 105 |
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|
| 106 |
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|
| 107 |
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| 108 |
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| 109 |
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"151656": {
|
| 110 |
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| 111 |
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| 112 |
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| 113 |
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| 114 |
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| 115 |
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| 116 |
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| 117 |
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| 118 |
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| 119 |
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| 120 |
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| 123 |
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| 124 |
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| 125 |
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| 126 |
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| 127 |
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| 128 |
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| 129 |
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| 130 |
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| 131 |
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| 132 |
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| 133 |
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| 134 |
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| 135 |
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| 136 |
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| 137 |
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| 138 |
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| 139 |
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| 140 |
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| 141 |
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| 142 |
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| 143 |
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| 144 |
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| 145 |
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| 146 |
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| 147 |
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| 148 |
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| 149 |
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|
| 150 |
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| 151 |
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| 152 |
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| 153 |
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| 154 |
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| 155 |
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| 156 |
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| 157 |
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|
| 158 |
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|
| 159 |
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|
| 160 |
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|
| 161 |
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|
| 162 |
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|
| 163 |
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|
| 164 |
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|
| 165 |
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|
| 166 |
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| 167 |
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| 168 |
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| 169 |
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| 170 |
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| 171 |
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| 172 |
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| 173 |
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| 174 |
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| 175 |
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| 176 |
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| 177 |
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| 178 |
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| 179 |
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| 180 |
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| 181 |
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| 182 |
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|
| 183 |
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|
| 184 |
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|
| 185 |
"<|object_ref_start|>",
|
|
|
|
| 194 |
"<|image_pad|>",
|
| 195 |
"<|video_pad|>"
|
| 196 |
],
|
| 197 |
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|
| 198 |
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"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
|
| 199 |
+
"clean_up_tokenization_spaces": false,
|
| 200 |
+
"eos_token": "<|im_end|>",
|
| 201 |
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|
| 202 |
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|
| 203 |
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|
| 204 |
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|
trainer_state.json
ADDED
|
@@ -0,0 +1,189 @@
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