Text Generation
Transformers
Safetensors
English
llama
Moderation
Safety
Filter
guardrail
prompt-injection
conversational
text-generation-inference
Instructions to use GeneralAnalysis/GA_Guard_1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GeneralAnalysis/GA_Guard_1B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="GeneralAnalysis/GA_Guard_1B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("GeneralAnalysis/GA_Guard_1B") model = AutoModelForCausalLM.from_pretrained("GeneralAnalysis/GA_Guard_1B", 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=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use GeneralAnalysis/GA_Guard_1B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "GeneralAnalysis/GA_Guard_1B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GeneralAnalysis/GA_Guard_1B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/GeneralAnalysis/GA_Guard_1B
- SGLang
How to use GeneralAnalysis/GA_Guard_1B 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 "GeneralAnalysis/GA_Guard_1B" \ --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": "GeneralAnalysis/GA_Guard_1B", "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 "GeneralAnalysis/GA_Guard_1B" \ --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": "GeneralAnalysis/GA_Guard_1B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use GeneralAnalysis/GA_Guard_1B with Docker Model Runner:
docker model run hf.co/GeneralAnalysis/GA_Guard_1B
Upload checkpoint 6543
Browse files- .gitattributes +1 -0
- README.md +33 -0
- chat_template.jinja +93 -0
- config.json +36 -0
- generation_config.json +14 -0
- model.safetensors +3 -0
- tokenizer.json +3 -0
- tokenizer_config.json +31 -0
- training_args.bin +3 -0
.gitattributes
CHANGED
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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@@ -0,0 +1,33 @@
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---
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base_model: meta-llama/Llama-3.2-1B-Instruct
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library_name: transformers
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tags:
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- llama
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- guard
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- generated_from_trainer
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- trl
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- sft
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---
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# GA Guard Llama
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Fine-tuned checkpoint from `meta-llama/Llama-3.2-1B-Instruct` for General Analysis guard classification.
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This upload uses checkpoint `sft_out/checkpoint-6543`. The chat template is the unchanged Llama 3.2 Instruct chat template used during training, and the tokenizer extends the base Llama vocabulary with 14 guard label special tokens.
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## Added Special Tokens
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- `<illicit_activities_violation>`
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- `<hate_and_abuse_violation>`
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- `<pii_and_ip_violation>`
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- `<prompt_security_violation>`
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- `<sexual_content_violation>`
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- `<misinformation_violation>`
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| 26 |
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- `<violence_and_self_harm_violation>`
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- `<illicit_activities_not_violation>`
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- `<hate_and_abuse_not_violation>`
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- `<pii_and_ip_not_violation>`
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- `<prompt_security_not_violation>`
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- `<sexual_content_not_violation>`
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- `<misinformation_not_violation>`
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- `<violence_and_self_harm_not_violation>`
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chat_template.jinja
ADDED
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@@ -0,0 +1,93 @@
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{{- bos_token }}
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{%- if custom_tools is defined %}
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{%- set tools = custom_tools %}
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{%- endif %}
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{%- if not tools_in_user_message is defined %}
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{%- set tools_in_user_message = true %}
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{%- endif %}
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| 8 |
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{%- if not date_string is defined %}
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{%- if strftime_now is defined %}
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{%- set date_string = strftime_now("%d %b %Y") %}
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{%- else %}
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{%- set date_string = "26 Jul 2024" %}
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{%- endif %}
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{%- endif %}
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{%- if not tools is defined %}
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{%- set tools = none %}
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{%- endif %}
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{#- This block extracts the system message, so we can slot it into the right place. #}
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| 20 |
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{%- if messages[0]['role'] == 'system' %}
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{%- set system_message = messages[0]['content']|trim %}
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| 22 |
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{%- set messages = messages[1:] %}
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{%- else %}
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{%- set system_message = "" %}
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{%- endif %}
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{#- System message #}
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{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
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{%- if tools is not none %}
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| 30 |
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{{- "Environment: ipython\n" }}
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{%- endif %}
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| 32 |
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{{- "Cutting Knowledge Date: December 2023\n" }}
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{{- "Today Date: " + date_string + "\n\n" }}
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| 34 |
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{%- if tools is not none and not tools_in_user_message %}
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| 35 |
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{{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
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| 36 |
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{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
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| 37 |
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{{- "Do not use variables.\n\n" }}
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| 38 |
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{%- for t in tools %}
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| 39 |
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{{- t | tojson(indent=4) }}
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| 40 |
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{{- "\n\n" }}
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| 41 |
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{%- endfor %}
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| 42 |
+
{%- endif %}
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| 43 |
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{{- system_message }}
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| 44 |
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{{- "<|eot_id|>" }}
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| 45 |
+
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| 46 |
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{#- Custom tools are passed in a user message with some extra guidance #}
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| 47 |
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{%- if tools_in_user_message and not tools is none %}
|
| 48 |
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{#- Extract the first user message so we can plug it in here #}
|
| 49 |
+
{%- if messages | length != 0 %}
|
| 50 |
+
{%- set first_user_message = messages[0]['content']|trim %}
|
| 51 |
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{%- set messages = messages[1:] %}
|
| 52 |
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{%- else %}
|
| 53 |
+
{{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
|
| 54 |
+
{%- endif %}
|
| 55 |
+
{{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
|
| 56 |
+
{{- "Given the following functions, please respond with a JSON for a function call " }}
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| 57 |
+
{{- "with its proper arguments that best answers the given prompt.\n\n" }}
|
| 58 |
+
{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
|
| 59 |
+
{{- "Do not use variables.\n\n" }}
|
| 60 |
+
{%- for t in tools %}
|
| 61 |
+
{{- t | tojson(indent=4) }}
|
| 62 |
+
{{- "\n\n" }}
|
| 63 |
+
{%- endfor %}
|
| 64 |
+
{{- first_user_message + "<|eot_id|>"}}
|
| 65 |
+
{%- endif %}
|
| 66 |
+
|
| 67 |
+
{%- for message in messages %}
|
| 68 |
+
{%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
|
| 69 |
+
{{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
|
| 70 |
+
{%- elif 'tool_calls' in message %}
|
| 71 |
+
{%- if not message.tool_calls|length == 1 %}
|
| 72 |
+
{{- raise_exception("This model only supports single tool-calls at once!") }}
|
| 73 |
+
{%- endif %}
|
| 74 |
+
{%- set tool_call = message.tool_calls[0].function %}
|
| 75 |
+
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
|
| 76 |
+
{{- '{"name": "' + tool_call.name + '", ' }}
|
| 77 |
+
{{- '"parameters": ' }}
|
| 78 |
+
{{- tool_call.arguments | tojson }}
|
| 79 |
+
{{- "}" }}
|
| 80 |
+
{{- "<|eot_id|>" }}
|
| 81 |
+
{%- elif message.role == "tool" or message.role == "ipython" %}
|
| 82 |
+
{{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
|
| 83 |
+
{%- if message.content is mapping or message.content is iterable %}
|
| 84 |
+
{{- message.content | tojson }}
|
| 85 |
+
{%- else %}
|
| 86 |
+
{{- message.content }}
|
| 87 |
+
{%- endif %}
|
| 88 |
+
{{- "<|eot_id|>" }}
|
| 89 |
+
{%- endif %}
|
| 90 |
+
{%- endfor %}
|
| 91 |
+
{%- if add_generation_prompt %}
|
| 92 |
+
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
|
| 93 |
+
{%- endif %}
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config.json
ADDED
|
@@ -0,0 +1,36 @@
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{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"LlamaForCausalLM"
|
| 4 |
+
],
|
| 5 |
+
"attention_bias": false,
|
| 6 |
+
"attention_dropout": 0.0,
|
| 7 |
+
"bos_token_id": 128000,
|
| 8 |
+
"dtype": "bfloat16",
|
| 9 |
+
"eos_token_id": 128009,
|
| 10 |
+
"head_dim": 64,
|
| 11 |
+
"hidden_act": "silu",
|
| 12 |
+
"hidden_size": 2048,
|
| 13 |
+
"initializer_range": 0.02,
|
| 14 |
+
"intermediate_size": 8192,
|
| 15 |
+
"max_position_embeddings": 131072,
|
| 16 |
+
"mlp_bias": false,
|
| 17 |
+
"model_type": "llama",
|
| 18 |
+
"num_attention_heads": 32,
|
| 19 |
+
"num_hidden_layers": 16,
|
| 20 |
+
"num_key_value_heads": 8,
|
| 21 |
+
"pad_token_id": 128009,
|
| 22 |
+
"pretraining_tp": 1,
|
| 23 |
+
"rms_norm_eps": 1e-05,
|
| 24 |
+
"rope_parameters": {
|
| 25 |
+
"factor": 32.0,
|
| 26 |
+
"high_freq_factor": 4.0,
|
| 27 |
+
"low_freq_factor": 1.0,
|
| 28 |
+
"original_max_position_embeddings": 8192,
|
| 29 |
+
"rope_theta": 500000.0,
|
| 30 |
+
"rope_type": "llama3"
|
| 31 |
+
},
|
| 32 |
+
"tie_word_embeddings": true,
|
| 33 |
+
"transformers_version": "5.7.0",
|
| 34 |
+
"use_cache": false,
|
| 35 |
+
"vocab_size": 128270
|
| 36 |
+
}
|
generation_config.json
ADDED
|
@@ -0,0 +1,14 @@
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| 1 |
+
{
|
| 2 |
+
"bos_token_id": 128000,
|
| 3 |
+
"do_sample": true,
|
| 4 |
+
"eos_token_id": [
|
| 5 |
+
128009,
|
| 6 |
+
128001,
|
| 7 |
+
128008,
|
| 8 |
+
128009
|
| 9 |
+
],
|
| 10 |
+
"pad_token_id": 128009,
|
| 11 |
+
"temperature": 0.6,
|
| 12 |
+
"top_p": 0.9,
|
| 13 |
+
"transformers_version": "5.7.0"
|
| 14 |
+
}
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:18b7d5ece96f1de9aaad93374542d8e83856239a69d1770b5904b9d180761885
|
| 3 |
+
size 2471702952
|
tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e7373f6790995360460d0a01508e17b1aa36f18f48b6c4019b3244901731485c
|
| 3 |
+
size 17212808
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,31 @@
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| 1 |
+
{
|
| 2 |
+
"backend": "tokenizers",
|
| 3 |
+
"bos_token": "<|begin_of_text|>",
|
| 4 |
+
"clean_up_tokenization_spaces": true,
|
| 5 |
+
"eos_token": "<|eot_id|>",
|
| 6 |
+
"extra_special_tokens": [
|
| 7 |
+
"<illicit_activities_violation>",
|
| 8 |
+
"<hate_and_abuse_violation>",
|
| 9 |
+
"<pii_and_ip_violation>",
|
| 10 |
+
"<prompt_security_violation>",
|
| 11 |
+
"<sexual_content_violation>",
|
| 12 |
+
"<misinformation_violation>",
|
| 13 |
+
"<violence_and_self_harm_violation>",
|
| 14 |
+
"<illicit_activities_not_violation>",
|
| 15 |
+
"<hate_and_abuse_not_violation>",
|
| 16 |
+
"<pii_and_ip_not_violation>",
|
| 17 |
+
"<prompt_security_not_violation>",
|
| 18 |
+
"<sexual_content_not_violation>",
|
| 19 |
+
"<misinformation_not_violation>",
|
| 20 |
+
"<violence_and_self_harm_not_violation>"
|
| 21 |
+
],
|
| 22 |
+
"is_local": false,
|
| 23 |
+
"local_files_only": false,
|
| 24 |
+
"model_input_names": [
|
| 25 |
+
"input_ids",
|
| 26 |
+
"attention_mask"
|
| 27 |
+
],
|
| 28 |
+
"model_max_length": 131072,
|
| 29 |
+
"pad_token": "<|eot_id|>",
|
| 30 |
+
"tokenizer_class": "TokenizersBackend"
|
| 31 |
+
}
|
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:26ef4fa9128f6f001de84f7423debfc65a138176d1013400732f1ed95ca90161
|
| 3 |
+
size 5713
|