Text Generation
Transformers
ExecuTorch
PyTorch
English
qwen2
function-calling
LLM Agent
tool-use
llama
qwen
LLaMA-factory
conversational
Instructions to use licongwei/xLAM-2-3b-fc-r-SpinQuant-ET with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use licongwei/xLAM-2-3b-fc-r-SpinQuant-ET with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="licongwei/xLAM-2-3b-fc-r-SpinQuant-ET") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("licongwei/xLAM-2-3b-fc-r-SpinQuant-ET") model = AutoModelForCausalLM.from_pretrained("licongwei/xLAM-2-3b-fc-r-SpinQuant-ET", 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 licongwei/xLAM-2-3b-fc-r-SpinQuant-ET with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "licongwei/xLAM-2-3b-fc-r-SpinQuant-ET" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "licongwei/xLAM-2-3b-fc-r-SpinQuant-ET", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/licongwei/xLAM-2-3b-fc-r-SpinQuant-ET
- SGLang
How to use licongwei/xLAM-2-3b-fc-r-SpinQuant-ET 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 "licongwei/xLAM-2-3b-fc-r-SpinQuant-ET" \ --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": "licongwei/xLAM-2-3b-fc-r-SpinQuant-ET", "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 "licongwei/xLAM-2-3b-fc-r-SpinQuant-ET" \ --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": "licongwei/xLAM-2-3b-fc-r-SpinQuant-ET", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use licongwei/xLAM-2-3b-fc-r-SpinQuant-ET with Docker Model Runner:
docker model run hf.co/licongwei/xLAM-2-3b-fc-r-SpinQuant-ET
| { | |
| "add_bos_token": false, | |
| "add_prefix_space": false, | |
| "added_tokens_decoder": { | |
| "151643": { | |
| "content": "<|endoftext|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151644": { | |
| "content": "<|im_start|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151645": { | |
| "content": "<|im_end|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151646": { | |
| "content": "<|object_ref_start|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151647": { | |
| "content": "<|object_ref_end|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151648": { | |
| "content": "<|box_start|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151649": { | |
| "content": "<|box_end|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151650": { | |
| "content": "<|quad_start|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151651": { | |
| "content": "<|quad_end|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151652": { | |
| "content": "<|vision_start|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151653": { | |
| "content": "<|vision_end|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151654": { | |
| "content": "<|vision_pad|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151655": { | |
| "content": "<|image_pad|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151656": { | |
| "content": "<|video_pad|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151657": { | |
| "content": "<tool_call>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "151658": { | |
| "content": "</tool_call>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "151659": { | |
| "content": "<|fim_prefix|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "151660": { | |
| "content": "<|fim_middle|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "151661": { | |
| "content": "<|fim_suffix|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
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| "special": false | |
| }, | |
| "151662": { | |
| "content": "<|fim_pad|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "151663": { | |
| "content": "<|repo_name|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "151664": { | |
| "content": "<|file_sep|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| } | |
| }, | |
| "additional_special_tokens": [ | |
| "<|im_start|>", | |
| "<|im_end|>", | |
| "<|object_ref_start|>", | |
| "<|object_ref_end|>", | |
| "<|box_start|>", | |
| "<|box_end|>", | |
| "<|quad_start|>", | |
| "<|quad_end|>", | |
| "<|vision_start|>", | |
| "<|vision_end|>", | |
| "<|vision_pad|>", | |
| "<|image_pad|>", | |
| "<|video_pad|>" | |
| ], | |
| "bos_token": null, | |
| "chat_template": "{# System message #}\n{{- \"<|im_start|>system\\n\" }}\n{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content'] | trim %}\n {%- set messages = messages[1:] %}\n {{- system_message + \"\\n\" }}\n{%- else %}\n {%- set system_message = \"You are a helpful assistant that can use tools. You are developed by Salesforce xLAM team.\" %}\n {% set format_instruction %}You have access to a set of tools. When using tools, make calls in a single JSON array: \n\n[{\"name\": \"tool_call_name\", \"arguments\": {\"arg1\": \"value1\", \"arg2\": \"value2\"}}, ... (additional parallel tool calls as needed)]\n\nIf no tool is suitable, state that explicitly. If the user's input lacks required parameters, ask for clarification. Do not interpret or respond until tool results are returned. Once they are available, process them or make additional calls if needed. For tasks that don't require tools, such as casual conversation or general advice, respond directly in plain text. The available tools are:{% endset %}\n {{- system_message + \"\\n\" }}\n {%- if tools is not none %}\n {{- format_instruction + \"\\n\\n\" }}\n {%- endif %}\n{%- endif %}\n\n{%- if tools is not none %}\n {%- for func in tools %}\n {{- func | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n{%- endif %}\n{{- \"<|im_end|>\" }}\n{%- for message in messages %}\n {%- if message['role'] == 'tool' %}\n {{- \"<|im_start|>tool\\n\" }}\n {%- if message.content is defined and message.content.content is defined %}\n {%- set content = message.content.content %}\n {%- else %}\n {%- set content = message.content %}\n {%- endif %}\n {%- if content is mapping or content is iterable and content is not string %}\n {{- content | tojson }}\n {%- else %}\n {{- content }}\n {%- endif %}\n {{- \"<|im_end|>\" }}\n {%- elif 'tool_calls' in message %}\n {{- \"<|im_start|>assistant\\n\" }}\n {%- if message['tool_calls'] %}\n {{- \"[\" }}\n {%- for tool_call in message.tool_calls %}\n {%- set out = tool_call.function | tojson %}\n {{- out }}\n {%- if not loop.last %}\n {{- \", \" }}\n {%- endif %}\n {%- endfor %}\n {{- \"]\"}}\n {%- elif message['content'] %}\n {{- message['content'] | trim }}\n {%- else %}\n {{- \"[]\\n\" }}\n {%- endif %}\n {{- \"<|im_end|>\" }}\n {%- else %}\n {{- \"<|im_start|>\" + message['role'] + \"\\n\" + message['content'] | trim + \"<|im_end|>\" }}\n {%- endif %}\n{%- endfor %}\n\n{%- if add_generation_prompt %}\n {{- \"<|im_start|>assistant\\n\" }}\n{%- endif %}\n", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|im_end|>", | |
| "errors": "replace", | |
| "model_max_length": 16384, | |
| "pad_token": "<|endoftext|>", | |
| "padding_side": "right", | |
| "split_special_tokens": false, | |
| "tokenizer_class": "Qwen2Tokenizer", | |
| "unk_token": null | |
| } | |