Text Generation
Transformers
Safetensors
English
bert
text-generation-inference
unsloth
trl
sft
conversational
Instructions to use jasong03/bert-emo-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jasong03/bert-emo-sft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="jasong03/bert-emo-sft") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("jasong03/bert-emo-sft") model = AutoModelForCausalLM.from_pretrained("jasong03/bert-emo-sft") 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
- vLLM
How to use jasong03/bert-emo-sft with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jasong03/bert-emo-sft" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jasong03/bert-emo-sft", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/jasong03/bert-emo-sft
- SGLang
How to use jasong03/bert-emo-sft 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 "jasong03/bert-emo-sft" \ --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": "jasong03/bert-emo-sft", "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 "jasong03/bert-emo-sft" \ --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": "jasong03/bert-emo-sft", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Unsloth Studio new
How to use jasong03/bert-emo-sft 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 jasong03/bert-emo-sft 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 jasong03/bert-emo-sft to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for jasong03/bert-emo-sft to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="jasong03/bert-emo-sft", max_seq_length=2048, ) - Docker Model Runner
How to use jasong03/bert-emo-sft with Docker Model Runner:
docker model run hf.co/jasong03/bert-emo-sft
Upload model trained with Unsloth
Browse filesUpload model trained with Unsloth 2x faster
- chat_template.jinja +144 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +57 -0
- vocab.txt +0 -0
chat_template.jinja
ADDED
|
@@ -0,0 +1,144 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
|
| 2 |
+
{%- if tools %}
|
| 3 |
+
{{- '<|im_start|>system
|
| 4 |
+
' }}
|
| 5 |
+
{%- if messages[0].role == 'system' %}
|
| 6 |
+
{{- messages[0].content + '
|
| 7 |
+
|
| 8 |
+
' }}
|
| 9 |
+
{%- endif %}
|
| 10 |
+
{{- "# Tools
|
| 11 |
+
|
| 12 |
+
You may call one or more functions to assist with the user query.
|
| 13 |
+
|
| 14 |
+
You are provided with function signatures within <tools></tools> XML tags:
|
| 15 |
+
<tools>" }}
|
| 16 |
+
{%- for tool in tools %}
|
| 17 |
+
{{- "
|
| 18 |
+
" }}
|
| 19 |
+
{{- tool | tojson }}
|
| 20 |
+
{%- endfor %}
|
| 21 |
+
{{- "
|
| 22 |
+
</tools>
|
| 23 |
+
|
| 24 |
+
For each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:
|
| 25 |
+
<tool_call>
|
| 26 |
+
{\"name\": <function-name>, \"arguments\": <args-json-object>}
|
| 27 |
+
</tool_call><|im_end|>
|
| 28 |
+
" }}
|
| 29 |
+
{%- else %}
|
| 30 |
+
{%- if messages[0].role == 'system' %}
|
| 31 |
+
{{- '<|im_start|>system
|
| 32 |
+
' + messages[0].content + '<|im_end|>
|
| 33 |
+
' }}
|
| 34 |
+
{%- endif %}
|
| 35 |
+
{%- endif %}
|
| 36 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 37 |
+
{%- for forward_message in messages %}
|
| 38 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 39 |
+
{%- set message = messages[index] %}
|
| 40 |
+
{%- set current_content = message.content if message.content is not none else '' %}
|
| 41 |
+
{%- set tool_start = '<tool_response>' %}
|
| 42 |
+
{%- set tool_start_length = tool_start|length %}
|
| 43 |
+
{%- set start_of_message = current_content[:tool_start_length] %}
|
| 44 |
+
{%- set tool_end = '</tool_response>' %}
|
| 45 |
+
{%- set tool_end_length = tool_end|length %}
|
| 46 |
+
{%- set start_pos = (current_content|length) - tool_end_length %}
|
| 47 |
+
{%- if start_pos < 0 %}
|
| 48 |
+
{%- set start_pos = 0 %}
|
| 49 |
+
{%- endif %}
|
| 50 |
+
{%- set end_of_message = current_content[start_pos:] %}
|
| 51 |
+
{%- if ns.multi_step_tool and message.role == "user" and not(start_of_message == tool_start and end_of_message == tool_end) %}
|
| 52 |
+
{%- set ns.multi_step_tool = false %}
|
| 53 |
+
{%- set ns.last_query_index = index %}
|
| 54 |
+
{%- endif %}
|
| 55 |
+
{%- endfor %}
|
| 56 |
+
{%- for message in messages %}
|
| 57 |
+
{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
|
| 58 |
+
{{- '<|im_start|>' + message.role + '
|
| 59 |
+
' + message.content + '<|im_end|>' + '
|
| 60 |
+
' }}
|
| 61 |
+
{%- elif message.role == "assistant" %}
|
| 62 |
+
{%- set content = message.content %}
|
| 63 |
+
{%- set reasoning_content = '' %}
|
| 64 |
+
{%- if message.reasoning_content is defined and message.reasoning_content is not none %}
|
| 65 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 66 |
+
{%- else %}
|
| 67 |
+
{%- if '</think>' in message.content %}
|
| 68 |
+
{%- set content = (message.content.split('</think>')|last).lstrip('
|
| 69 |
+
') %}
|
| 70 |
+
{%- set reasoning_content = (message.content.split('</think>')|first).rstrip('
|
| 71 |
+
') %}
|
| 72 |
+
{%- set reasoning_content = (reasoning_content.split('<think>')|last).lstrip('
|
| 73 |
+
') %}
|
| 74 |
+
{%- endif %}
|
| 75 |
+
{%- endif %}
|
| 76 |
+
{%- if loop.index0 > ns.last_query_index %}
|
| 77 |
+
{%- if loop.last or (not loop.last and reasoning_content) %}
|
| 78 |
+
{{- '<|im_start|>' + message.role + '
|
| 79 |
+
<think>
|
| 80 |
+
' + reasoning_content.strip('
|
| 81 |
+
') + '
|
| 82 |
+
</think>
|
| 83 |
+
|
| 84 |
+
' + content.lstrip('
|
| 85 |
+
') }}
|
| 86 |
+
{%- else %}
|
| 87 |
+
{{- '<|im_start|>' + message.role + '
|
| 88 |
+
' + content }}
|
| 89 |
+
{%- endif %}
|
| 90 |
+
{%- else %}
|
| 91 |
+
{{- '<|im_start|>' + message.role + '
|
| 92 |
+
' + content }}
|
| 93 |
+
{%- endif %}
|
| 94 |
+
{%- if message.tool_calls %}
|
| 95 |
+
{%- for tool_call in message.tool_calls %}
|
| 96 |
+
{%- if (loop.first and content) or (not loop.first) %}
|
| 97 |
+
{{- '
|
| 98 |
+
' }}
|
| 99 |
+
{%- endif %}
|
| 100 |
+
{%- if tool_call.function %}
|
| 101 |
+
{%- set tool_call = tool_call.function %}
|
| 102 |
+
{%- endif %}
|
| 103 |
+
{{- '<tool_call>
|
| 104 |
+
{"name": "' }}
|
| 105 |
+
{{- tool_call.name }}
|
| 106 |
+
{{- '", "arguments": ' }}
|
| 107 |
+
{%- if tool_call.arguments is string %}
|
| 108 |
+
{{- tool_call.arguments }}
|
| 109 |
+
{%- else %}
|
| 110 |
+
{{- tool_call.arguments | tojson }}
|
| 111 |
+
{%- endif %}
|
| 112 |
+
{{- '}
|
| 113 |
+
</tool_call>' }}
|
| 114 |
+
{%- endfor %}
|
| 115 |
+
{%- endif %}
|
| 116 |
+
{{- '<|im_end|>
|
| 117 |
+
' }}
|
| 118 |
+
{%- elif message.role == "tool" %}
|
| 119 |
+
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
| 120 |
+
{{- '<|im_start|>user' }}
|
| 121 |
+
{%- endif %}
|
| 122 |
+
{{- '
|
| 123 |
+
<tool_response>
|
| 124 |
+
' }}
|
| 125 |
+
{{- message.content }}
|
| 126 |
+
{{- '
|
| 127 |
+
</tool_response>' }}
|
| 128 |
+
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
| 129 |
+
{{- '<|im_end|>
|
| 130 |
+
' }}
|
| 131 |
+
{%- endif %}
|
| 132 |
+
{%- endif %}
|
| 133 |
+
{%- endfor %}
|
| 134 |
+
{%- if add_generation_prompt %}
|
| 135 |
+
{{- '<|im_start|>assistant
|
| 136 |
+
' }}
|
| 137 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 138 |
+
{{- '<think>
|
| 139 |
+
|
| 140 |
+
</think>
|
| 141 |
+
|
| 142 |
+
' }}
|
| 143 |
+
{%- endif %}
|
| 144 |
+
{%- endif %}
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"cls_token": "[CLS]",
|
| 3 |
+
"mask_token": "[MASK]",
|
| 4 |
+
"pad_token": "[PAD]",
|
| 5 |
+
"sep_token": "[SEP]",
|
| 6 |
+
"unk_token": "[UNK]"
|
| 7 |
+
}
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,57 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"added_tokens_decoder": {
|
| 3 |
+
"0": {
|
| 4 |
+
"content": "[PAD]",
|
| 5 |
+
"lstrip": false,
|
| 6 |
+
"normalized": false,
|
| 7 |
+
"rstrip": false,
|
| 8 |
+
"single_word": false,
|
| 9 |
+
"special": true
|
| 10 |
+
},
|
| 11 |
+
"100": {
|
| 12 |
+
"content": "[UNK]",
|
| 13 |
+
"lstrip": false,
|
| 14 |
+
"normalized": false,
|
| 15 |
+
"rstrip": false,
|
| 16 |
+
"single_word": false,
|
| 17 |
+
"special": true
|
| 18 |
+
},
|
| 19 |
+
"101": {
|
| 20 |
+
"content": "[CLS]",
|
| 21 |
+
"lstrip": false,
|
| 22 |
+
"normalized": false,
|
| 23 |
+
"rstrip": false,
|
| 24 |
+
"single_word": false,
|
| 25 |
+
"special": true
|
| 26 |
+
},
|
| 27 |
+
"102": {
|
| 28 |
+
"content": "[SEP]",
|
| 29 |
+
"lstrip": false,
|
| 30 |
+
"normalized": false,
|
| 31 |
+
"rstrip": false,
|
| 32 |
+
"single_word": false,
|
| 33 |
+
"special": true
|
| 34 |
+
},
|
| 35 |
+
"103": {
|
| 36 |
+
"content": "[MASK]",
|
| 37 |
+
"lstrip": false,
|
| 38 |
+
"normalized": false,
|
| 39 |
+
"rstrip": false,
|
| 40 |
+
"single_word": false,
|
| 41 |
+
"special": true
|
| 42 |
+
}
|
| 43 |
+
},
|
| 44 |
+
"clean_up_tokenization_spaces": false,
|
| 45 |
+
"cls_token": "[CLS]",
|
| 46 |
+
"do_lower_case": false,
|
| 47 |
+
"extra_special_tokens": {},
|
| 48 |
+
"mask_token": "[MASK]",
|
| 49 |
+
"model_max_length": 512,
|
| 50 |
+
"pad_token": "[PAD]",
|
| 51 |
+
"padding_side": "left",
|
| 52 |
+
"sep_token": "[SEP]",
|
| 53 |
+
"strip_accents": null,
|
| 54 |
+
"tokenize_chinese_chars": true,
|
| 55 |
+
"tokenizer_class": "BertTokenizer",
|
| 56 |
+
"unk_token": "[UNK]"
|
| 57 |
+
}
|
vocab.txt
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|