Upload Biomni-R0-32B-AWQ-INT4 - quantized variant of Biomni-R0-32B-Preview

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,84 @@
+---
+license: apache-2.0
+base_model: biomni/Biomni-R0-32B-Preview
+tags:
+  - quantized
+  - awq
+  - int4
+  - 4-bit
+  - medical
+  - biomedical
+  - reasoning
+  - llmcompressor
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+# Biomni-R0-32B-AWQ-INT4
+
+This is an **AWQ INT4 quantized** version of [Biomni-R0-32B-Preview](https://huggingface.co/biomni/Biomni-R0-32B-Preview).
+
+## Quantization Details
+
+| Parameter | Value |
+|-----------|-------|
+| **Scheme** | W4A16 (4-bit weights, 16-bit activations) |
+| **Method** | AWQ (Activation-aware Weight Quantization) |
+| **Group Size** | 128 |
+| **Calibration** | Custom biomedical dataset |
+| **Framework** | LLM Compressor |
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained(
+    "hassanshka/Biomni-R0-32B-AWQ-INT4",
+    device_map="auto",
+    torch_dtype="auto",
+    trust_remote_code=True
+)
+tokenizer = AutoTokenizer.from_pretrained("hassanshka/Biomni-R0-32B-AWQ-INT4")
+
+# Inference
+messages = [{"role": "user", "content": "Your medical question here"}]
+inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to(model.device)
+outputs = model.generate(inputs, max_new_tokens=512)
+print(tokenizer.decode(outputs[0]))
+```
+
+## Quantization Script
+
+```python
+from llmcompressor.modifiers.awq import AWQModifier
+from llmcompressor import oneshot
+
+recipe = AWQModifier(
+    scheme="W4A16",
+    targets="Linear",
+    ignore=["lm_head"],
+)
+
+oneshot(
+    model=model,
+    dataset=calibration_data,
+    recipe=recipe,
+    max_seq_length=2048,
+    num_calibration_samples=len(calibration_data),
+)
+```
+
+## Performance
+
+- **Memory Reduction**: ~75% compared to BF16
+- **Inference Speed**: Optimized for consumer GPUs (RTX 3090/4090)
+- **Accuracy**: Minimal degradation due to custom calibration on biomedical data
+
+## License
+
+Apache 2.0 (same as base model)
+
+## Citation
+
+If you use this model, please cite the original Biomni model.

added_tokens.json

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+{
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+  "</tool_call>": 151658,
+  "</tool_response>": 151666,
+  "<think>": 151667,
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+  "<|vision_pad|>": 151654,
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+}

chat_template.jinja

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}
+{%- for message in messages %}
+    {%- if message.content is string %}
+        {%- set content = message.content %}
+    {%- else %}
+        {%- set content = '' %}
+    {%- endif %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- endif %}
+{%- endif %}

config.json

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+{
+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
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+  "attention_dropout": 0.0,
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+  "dtype": "float32",
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+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 5120,
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+  "intermediate_size": 25600,
+  "layer_types": [
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+  "max_window_layers": 64,
+  "model_type": "qwen3",
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+  "num_hidden_layers": 64,
+  "num_key_value_heads": 8,
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+        "targets": [
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+          "dynamic": false,
+          "group_size": 128,
+          "num_bits": 4,
+          "observer": "minmax",
+          "observer_kwargs": {},
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+          "symmetric": true,
+          "type": "int"
+        }
+      }
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+    "global_compression_ratio": null,
+    "ignore": [
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+    "quant_method": "compressed-tensors",
+    "quantization_status": "compressed",
+    "sparsity_config": {},
+    "transform_config": {},
+    "version": "0.12.2"
+  },
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "transformers_version": "4.56.2",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

generation_config.json

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+  "_from_model_config": true,
+  "bos_token_id": 151643,
+  "eos_token_id": 151645,
+  "transformers_version": "4.56.2"
+}

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recipe.yaml

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+default_stage:
+  default_modifiers:
+    AWQModifier:
+      targets: [Linear]
+      ignore: [lm_head]
+      scheme: W4A16
+      mappings:
+      - smooth_layer: re:.*input_layernorm$
+        balance_layers: ['re:.*q_proj$', 're:.*k_proj$', 're:.*v_proj$']
+      - smooth_layer: re:.*v_proj$
+        balance_layers: ['re:.*o_proj$']
+      - smooth_layer: re:.*post_attention_layernorm$
+        balance_layers: ['re:.*gate_proj$', 're:.*up_proj$']
+      - smooth_layer: re:.*up_proj$
+        balance_layers: ['re:.*down_proj$']
+      duo_scaling: true

special_tokens_map.json

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+{
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+    "<|im_end|>",
+    "<|object_ref_start|>",
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+}

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tokenizer_config.json

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+  "errors": "replace",
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+}