Text Generation
Transformers
Safetensors
English
qwen3
esper
esper-3
valiant
valiant-labs
qwen
qwen-3
qwen-3-8b
8b
deepseek
deepseek-r1-0528
deepseek-r1
reasoning
code
code-instruct
python
javascript
dev-ops
jenkins
terraform
scripting
powershell
azure
aws
gcp
cloud
problem-solving
architect
engineer
developer
creative
analytical
expert
rationality
conversational
chat
instruct
text-generation-inference
Upload folder using huggingface_hub
Browse files- README.md +129 -0
- config.json +35 -0
- model-00001-of-00007.safetensors +3 -0
- model-00002-of-00007.safetensors +3 -0
- model-00003-of-00007.safetensors +3 -0
- model-00004-of-00007.safetensors +3 -0
- model-00005-of-00007.safetensors +3 -0
- model-00006-of-00007.safetensors +3 -0
- model-00007-of-00007.safetensors +3 -0
- model.safetensors.index.json +406 -0
- tokenizer.json +0 -0
- tokenizer_config.json +35 -0
README.md
ADDED
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---
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language:
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- en
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- esper
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- esper-3
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- valiant
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- valiant-labs
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- qwen
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- qwen-3
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- qwen-3-8b
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- 8b
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- deepseek
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- deepseek-r1-0528
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- deepseek-r1
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- reasoning
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- code
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- code-instruct
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- python
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- javascript
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- dev-ops
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- jenkins
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- terraform
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- scripting
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- powershell
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- azure
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- aws
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- gcp
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- cloud
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- problem-solving
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- architect
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- engineer
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- developer
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- creative
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- analytical
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- expert
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- rationality
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- conversational
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- chat
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- instruct
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base_model: deepseek-ai/DeepSeek-R1-0528-Qwen3-8B
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datasets:
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- sequelbox/Titanium2.1-DeepSeek-R1
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- sequelbox/Tachibana2-DeepSeek-R1
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- sequelbox/Raiden-DeepSeek-R1
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license: apache-2.0
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---
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**[Support our open-source dataset and model releases!](https://huggingface.co/spaces/sequelbox/SupportOpenSource)**
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Esper 3: [DeepSeek-R1-0528-Qwen3-8B](https://huggingface.co/ValiantLabs/DeepSeek-R1-0528-Qwen3-8B-Esper3), [Qwen3-4B](https://huggingface.co/ValiantLabs/Qwen3-4B-Esper3), [Qwen3-8B](https://huggingface.co/ValiantLabs/Qwen3-8B-Esper3), [Qwen3-14B](https://huggingface.co/ValiantLabs/Qwen3-14B-Esper3)
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Esper 3 is a coding, architecture, and DevOps reasoning specialist built on Qwen 3.
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- Finetuned on our [DevOps and architecture reasoning](https://huggingface.co/datasets/sequelbox/Titanium2.1-DeepSeek-R1) and [code reasoning](https://huggingface.co/datasets/sequelbox/Tachibana2-DeepSeek-R1) data generated with Deepseek R1!
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- Improved [general and creative reasoning](https://huggingface.co/datasets/sequelbox/Raiden-DeepSeek-R1) to supplement problem-solving and general chat performance.
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- Small model sizes allow running on local desktop and mobile, plus super-fast server inference!
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## Prompting Guide
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Esper 3 uses the [DeepSeek-R1-0528-Qwen3-8B](https://huggingface.co/deepseek-ai/DeepSeek-R1-0528-Qwen3-8B) prompt format.
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Esper 3 is a reasoning finetune; **we recommend enable_thinking=True for all chats.**
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Example inference script to get started:
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "ValiantLabs/DeepSeek-R1-0528-Qwen3-8B-Esper3"
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# load the tokenizer and the model
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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torch_dtype="auto",
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device_map="auto"
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)
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# prepare the model input
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prompt = "Write a Terraform configuration that uses the `aws_ami` data source to find the latest Amazon Linux 2 AMI. Then, provision an EC2 instance using this dynamically determined AMI ID."
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messages = [
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{"role": "user", "content": prompt}
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]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True,
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enable_thinking=True # Switches between thinking and non-thinking modes. Default is True.
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)
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model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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# conduct text completion
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generated_ids = model.generate(
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**model_inputs,
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max_new_tokens=32768
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)
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output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist()
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# parsing thinking content
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try:
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# rindex finding 151668 (</think>)
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index = len(output_ids) - output_ids[::-1].index(151668)
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except ValueError:
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index = 0
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thinking_content = tokenizer.decode(output_ids[:index], skip_special_tokens=True).strip("\n")
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content = tokenizer.decode(output_ids[index:], skip_special_tokens=True).strip("\n")
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print("thinking content:", thinking_content)
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print("content:", content)
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```
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Esper 3 is created by [Valiant Labs.](http://valiantlabs.ca/)
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[Check out our HuggingFace page to see all of our models!](https://huggingface.co/ValiantLabs)
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We care about open source. For everyone to use.
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config.json
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{
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"architectures": [
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"Qwen3ForCausalLM"
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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": 151643,
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"eos_token_id": 151645,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 12288,
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"max_position_embeddings": 131072,
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"max_window_layers": 36,
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"model_type": "qwen3",
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"num_attention_heads": 32,
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"num_hidden_layers": 36,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-06,
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"rope_scaling": {
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"attn_factor": 0.8782488562869419,
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"factor": 4.0,
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"original_max_position_embeddings": 32768,
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"rope_type": "yarn"
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},
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"rope_theta": 1000000,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"torch_dtype": "float32",
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"transformers_version": "4.52.3",
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"use_cache": true,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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model-00001-of-00007.safetensors
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version https://git-lfs.github.com/spec/v1
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size 4972454376
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model-00002-of-00007.safetensors
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model-00003-of-00007.safetensors
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model-00004-of-00007.safetensors
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model-00005-of-00007.safetensors
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model-00006-of-00007.safetensors
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model-00007-of-00007.safetensors
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model.safetensors.index.json
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|
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|
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|
404 |
+
"model.norm.weight": "model-00007-of-00007.safetensors"
|
405 |
+
}
|
406 |
+
}
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tokenizer.json
ADDED
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tokenizer_config.json
ADDED
@@ -0,0 +1,35 @@
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{
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+
"add_bos_token": false,
|
3 |
+
"add_eos_token": false,
|
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+
"bos_token": {
|
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+
"__type": "AddedToken",
|
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+
"content": "<|begin▁of▁sentence|>",
|
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+
"lstrip": false,
|
8 |
+
"normalized": true,
|
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+
"rstrip": false,
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+
"single_word": false
|
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+
},
|
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+
"clean_up_tokenization_spaces": false,
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+
"eos_token": {
|
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+
"__type": "AddedToken",
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+
"content": "<|end▁of▁sentence|>",
|
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+
"lstrip": false,
|
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+
"normalized": true,
|
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+
"rstrip": false,
|
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+
"single_word": false
|
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+
},
|
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+
"legacy": true,
|
22 |
+
"model_max_length": 131072,
|
23 |
+
"pad_token": {
|
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+
"__type": "AddedToken",
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+
"content": "<|end▁of▁sentence|>",
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+
"lstrip": false,
|
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+
"normalized": true,
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+
"rstrip": false,
|
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+
"single_word": false
|
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+
},
|
31 |
+
"sp_model_kwargs": {},
|
32 |
+
"unk_token": null,
|
33 |
+
"tokenizer_class": "LlamaTokenizerFast",
|
34 |
+
"chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='', is_first_sp=true, is_last_user=false) %}{%- for message in messages %}{%- if message['role'] == 'system' %}{%- if ns.is_first_sp %}{% set ns.system_prompt = ns.system_prompt + message['content'] %}{% set ns.is_first_sp = false %}{%- else %}{% set ns.system_prompt = ns.system_prompt + '\n\n' + message['content'] %}{%- endif %}{%- endif %}{%- endfor %}{{ bos_token }}{{ ns.system_prompt }}{%- for message in messages %}{% set content = message['content'] %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{%- set ns.is_first = false -%}{%- set ns.is_last_user = true -%}{{'<|User|>' + content + '<|Assistant|>'}}{%- endif %}{%- if message['role'] == 'assistant' %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{% endif %}{%- if message['role'] == 'assistant' and message['tool_calls'] is defined and message['tool_calls'] is not none %}{%- set ns.is_last_user = false -%}{%- if ns.is_tool %}{{'<|tool▁outputs▁end|>'}}{%- endif %}{%- set ns.is_first = false %}{%- set ns.is_tool = false -%}{%- set ns.is_output_first = true %}{%- for tool in message['tool_calls'] %}{%- if not ns.is_first %}{%- if content is none %}{{'<|tool▁calls▁begin|><|tool▁call▁begin|>' + tool['type'] + '<|tool▁sep|>' + tool['function']['name'] + '\n' + '```json' + '\n' + tool['function']['arguments'] + '\n' + '```' + '<|tool▁call▁end|>'}}{%- else %}{{content + '<|tool▁calls▁begin|><|tool▁call▁begin|>' + tool['type'] + '<|tool▁sep|>' + tool['function']['name'] + '\n' + '```json' + '\n' + tool['function']['arguments'] + '\n' + '```' + '<|tool▁call▁end|>'}}{%- endif %}{%- set ns.is_first = true -%}{%- else %}{{'\n' + '<|tool▁call▁begin|>' + tool['type'] + '<|tool▁sep|>' + tool['function']['name'] + '\n' + '```json' + '\n' + tool['function']['arguments'] + '\n' + '```' + '<|tool▁call▁end|>'}}{%- endif %}{%- endfor %}{{'<|tool▁calls▁end|><|end▁of▁sentence|>'}}{%- endif %}{%- if message['role'] == 'assistant' and (message['tool_calls'] is not defined or message['tool_calls'] is none)%}{%- set ns.is_last_user = false -%}{%- if ns.is_tool %}{{'<|tool▁outputs▁end|>' + content + '<|end▁of▁sentence|>'}}{%- set ns.is_tool = false -%}{%- else %}{{content + '<|end▁of▁sentence|>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_last_user = false -%}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<|tool▁outputs▁begin|><|tool▁output▁begin|>' + content + '<|tool▁output▁end|>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\n<|tool▁output▁begin|>' + content + '<|tool▁output▁end|>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<|tool▁outputs▁end|>'}}{% endif %}{% if add_generation_prompt and not ns.is_last_user and not ns.is_tool %}{{'<|Assistant|>'}}{% endif %}"
|
35 |
+
}
|