Initial upload: Qwen3.6-35B-A3B xLAM Function-Calling LoRA

README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen3.6-35B-A3B
+tags:
+  - lora
+  - peft
+  - qwen
+  - qwen3
+  - function-calling
+  - tool-use
+  - xlam
+datasets:
+  - minpeter/xlam-function-calling-60k-parsed
+library_name: peft
+---
+
+# Qwen3.6-35B-A3B xLAM Function-Calling LoRA
+
+A LoRA adapter fine-tuned on `minpeter/xlam-function-calling-60k-parsed` from the `Qwen/Qwen3.6-35B-A3B` base model.
+
+## Training configuration
+
+- **Method:** LoRA (bf16)
+- **LoRA rank (r):** 64
+- **LoRA alpha:** 128
+- **Dataset:** minpeter/xlam-function-calling-60k-parsed
+- **Infrastructure:** NVIDIA Run:AI on Amazon SageMaker HyperPod (EKS mode)
+
+## Usage with transformers + peft
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+import torch
+
+base = AutoModelForCausalLM.from_pretrained(
+    "Qwen/Qwen3.6-35B-A3B",
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+model = PeftModel.from_pretrained(base, "ying2022/qwen3-6-35b-xlam-tools-lora")
+tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3.6-35B-A3B")
+
+messages = [{"role": "user", "content": "<your prompt here>"}]
+inputs = tokenizer.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True).to(model.device)
+outputs = model.generate(inputs, max_new_tokens=500, temperature=0.3)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Serving with vLLM
+
+```bash
+vllm serve Qwen/Qwen3.6-35B-A3B \
+  --enable-lora \
+  --lora-modules adapter=ying2022/qwen3-6-35b-xlam-tools-lora \
+  --max-loras 1 --max-lora-rank 64 \
+  --tensor-parallel-size 2 \
+  --gpu-memory-utilization 0.90 \
+  --max-model-len 4096
+```

adapter_config.json

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+{
+  "peft_type": "LORA",
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen3.6-35B-A3B",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "lora_alpha": 128,
+  "lora_dropout": 0.0,
+  "modules_to_save": null,
+  "r": 64,
+  "rank_pattern": {},
+  "alpha_pattern": {},
+  "target_modules": [
+    "k_proj",
+    "o_proj",
+    "proj",
+    "q_proj",
+    "qkv",
+    "v_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+oid sha256:45e93de80a9b1db532d4d64f148203298854ea60d628fe67525083f05fef3bee
+size 108358512