Text Classification
Transformers
ONNX
Safetensors
GGUF
intent-classification
tool-routing
llama.cpp
onnxruntime
conversational
Instructions to use kon171verma/intent-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kon171verma/intent-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kon171verma/intent-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kon171verma/intent-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use kon171verma/intent-classifier with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf kon171verma/intent-classifier:Q4_K_M # Run inference directly in the terminal: llama cli -hf kon171verma/intent-classifier:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf kon171verma/intent-classifier:Q4_K_M # Run inference directly in the terminal: llama cli -hf kon171verma/intent-classifier:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf kon171verma/intent-classifier:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf kon171verma/intent-classifier:Q4_K_M
Use Docker
docker model run hf.co/kon171verma/intent-classifier:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use kon171verma/intent-classifier with Ollama:
ollama run hf.co/kon171verma/intent-classifier:Q4_K_M
- Unsloth Desktop
- Pi
How to use kon171verma/intent-classifier with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf kon171verma/intent-classifier:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "kon171verma/intent-classifier:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use kon171verma/intent-classifier with Docker Model Runner:
docker model run hf.co/kon171verma/intent-classifier:Q4_K_M
- Lemonade
How to use kon171verma/intent-classifier with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull kon171verma/intent-classifier:Q4_K_M
Run and chat with the model
lemonade run user.intent-classifier-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use kon171verma/intent-classifier with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf kon171verma/intent-classifier:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default kon171verma/intent-classifier:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use kon171verma/intent-classifier with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf kon171verma/intent-classifier:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "kon171verma/intent-classifier:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Konark Verma commited on
Delete llama3.2-1b
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{%- set date_string = "26 Jul 2024" %}
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| 13 |
-
{%- endif %}
|
| 14 |
-
{%- endif %}
|
| 15 |
-
{%- if not tools is defined %}
|
| 16 |
-
{%- set tools = none %}
|
| 17 |
-
{%- endif %}
|
| 18 |
-
|
| 19 |
-
{#- This block extracts the system message, so we can slot it into the right place. #}
|
| 20 |
-
{%- if messages[0]['role'] == 'system' %}
|
| 21 |
-
{%- set system_message = messages[0]['content']|trim %}
|
| 22 |
-
{%- set messages = messages[1:] %}
|
| 23 |
-
{%- else %}
|
| 24 |
-
{%- set system_message = "" %}
|
| 25 |
-
{%- endif %}
|
| 26 |
-
|
| 27 |
-
{#- System message #}
|
| 28 |
-
{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
|
| 29 |
-
{%- if tools is not none %}
|
| 30 |
-
{{- "Environment: ipython\n" }}
|
| 31 |
-
{%- endif %}
|
| 32 |
-
{{- "Cutting Knowledge Date: December 2023\n" }}
|
| 33 |
-
{{- "Today Date: " + date_string + "\n\n" }}
|
| 34 |
-
{%- if tools is not none and not tools_in_user_message %}
|
| 35 |
-
{{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
|
| 36 |
-
{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
|
| 37 |
-
{{- "Do not use variables.\n\n" }}
|
| 38 |
-
{%- for t in tools %}
|
| 39 |
-
{{- t | tojson(indent=4) }}
|
| 40 |
-
{{- "\n\n" }}
|
| 41 |
-
{%- endfor %}
|
| 42 |
-
{%- endif %}
|
| 43 |
-
{{- system_message }}
|
| 44 |
-
{{- "<|eot_id|>" }}
|
| 45 |
-
|
| 46 |
-
{#- Custom tools are passed in a user message with some extra guidance #}
|
| 47 |
-
{%- if tools_in_user_message and not tools is none %}
|
| 48 |
-
{#- 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 |
-
{%- set messages = messages[1:] %}
|
| 52 |
-
{%- 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 " }}
|
| 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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|
llama3.2-1b/safetensors/config.json
DELETED
|
@@ -1,40 +0,0 @@
|
|
| 1 |
-
{
|
| 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": [
|
| 10 |
-
128001,
|
| 11 |
-
128008,
|
| 12 |
-
128009
|
| 13 |
-
],
|
| 14 |
-
"head_dim": 64,
|
| 15 |
-
"hidden_act": "silu",
|
| 16 |
-
"hidden_size": 2048,
|
| 17 |
-
"initializer_range": 0.02,
|
| 18 |
-
"intermediate_size": 8192,
|
| 19 |
-
"max_position_embeddings": 131072,
|
| 20 |
-
"mlp_bias": false,
|
| 21 |
-
"model_type": "llama",
|
| 22 |
-
"num_attention_heads": 32,
|
| 23 |
-
"num_hidden_layers": 16,
|
| 24 |
-
"num_key_value_heads": 8,
|
| 25 |
-
"pad_token_id": null,
|
| 26 |
-
"pretraining_tp": 1,
|
| 27 |
-
"rms_norm_eps": 1e-05,
|
| 28 |
-
"rope_parameters": {
|
| 29 |
-
"factor": 32.0,
|
| 30 |
-
"high_freq_factor": 4.0,
|
| 31 |
-
"low_freq_factor": 1.0,
|
| 32 |
-
"original_max_position_embeddings": 8192,
|
| 33 |
-
"rope_theta": 500000.0,
|
| 34 |
-
"rope_type": "llama3"
|
| 35 |
-
},
|
| 36 |
-
"tie_word_embeddings": true,
|
| 37 |
-
"transformers_version": "5.14.1",
|
| 38 |
-
"use_cache": true,
|
| 39 |
-
"vocab_size": 128256
|
| 40 |
-
}
|
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|
llama3.2-1b/safetensors/generation_config.json
DELETED
|
@@ -1,12 +0,0 @@
|
|
| 1 |
-
{
|
| 2 |
-
"bos_token_id": 128000,
|
| 3 |
-
"do_sample": true,
|
| 4 |
-
"eos_token_id": [
|
| 5 |
-
128001,
|
| 6 |
-
128008,
|
| 7 |
-
128009
|
| 8 |
-
],
|
| 9 |
-
"temperature": 0.6,
|
| 10 |
-
"top_p": 0.9,
|
| 11 |
-
"transformers_version": "5.14.1"
|
| 12 |
-
}
|
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|
llama3.2-1b/safetensors/model.safetensors
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:88fcfc6aebbcb6ddad93b7818511f8637ba5e8a704455693349625e9d4d6138d
|
| 3 |
-
size 2471645608
|
|
|
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|
llama3.2-1b/safetensors/tokenizer.json
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:6b9e4e7fb171f92fd137b777cc2714bf87d11576700a1dcd7a399e7bbe39537b
|
| 3 |
-
size 17209920
|
|
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|
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|
|
llama3.2-1b/safetensors/tokenizer_config.json
DELETED
|
@@ -1,14 +0,0 @@
|
|
| 1 |
-
{
|
| 2 |
-
"backend": "tokenizers",
|
| 3 |
-
"bos_token": "<|begin_of_text|>",
|
| 4 |
-
"clean_up_tokenization_spaces": true,
|
| 5 |
-
"eos_token": "<|eot_id|>",
|
| 6 |
-
"is_local": false,
|
| 7 |
-
"local_files_only": false,
|
| 8 |
-
"model_input_names": [
|
| 9 |
-
"input_ids",
|
| 10 |
-
"attention_mask"
|
| 11 |
-
],
|
| 12 |
-
"model_max_length": 131072,
|
| 13 |
-
"tokenizer_class": "TokenizersBackend"
|
| 14 |
-
}
|
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