Update README

README.md

@@ -12,6 +12,120 @@ tags:
 - sft
 ---
 
+# Model Information
+
+The `cmd2cwl` model is an instruction fine-tuned version of the `unsloth/Llama-3.2-3B`. This model has been trained on a custom dataset consisting of help documentation from various command-line tools and corresponding CWL (Common Workflow Language) scripts. Its purpose is to assist users in converting command-line tool documentation into clean and well-structured CWL scripts, enhancing automation and workflow reproducibility.
+
+# Example
+## Task
+``` python
+question = """
+Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
+
+### Instruction:
+Write a cwl script for md5sum with docker image alpine.
+
+### Input:
+
+    With no FILE, or when FILE is -, read standard input.
+
+    -b, --binary         read in binary mode
+    -c, --check          read MD5 sums from the FILEs and check them
+    --tag            create a BSD-style checksum
+    -t, --text           read in text mode (default)
+    -z, --zero           end each output line with NUL, not newline,
+    and disable file name escaping
+
+    The following five options are useful only when verifying checksums:
+    --ignore-missing  don't fail or report status for missing files
+    --quiet          don't print OK for each successfully verified file
+    --status         don't output anything, status code shows success
+    --strict         exit non-zero for improperly formatted checksum lines
+    -w, --warn           warn about improperly formatted checksum lines
+
+    --help     display this help and exit
+    --version  output version information and exit
+
+    The sums are computed as described in RFC 1321.  When checking, the input
+    should be a former output of this program.  The default mode is to print a
+    line with checksum, a space, a character indicating input mode ('*' for binary,
+    ' ' for text or where binary is insignificant), and name for each FILE.
+
+
+### Response:
+"""
+```
+
+## Using unsloth
+
+``` python
+from unsloth import FastLanguageModel
+from transformers import TextStreamer
+
+model, tokenizer = FastLanguageModel.from_pretrained(
+    model_name = "hubentu/cmd2cwl_Llama-3.2-3B",
+    load_in_4bit = False,
+)
+FastLanguageModel.for_inference(model)
+
+inputs = tokenizer(
+    [question],
+    return_tensors = "pt").to("cuda")
+
+text_streamer = TextStreamer(tokenizer)
+_ = model.generate(**inputs, streamer = text_streamer)
+
+```
+
+## Using AutoModelForCausalLM
+``` python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from transformers import TextStreamer
+
+model = AutoModelForCausalLM.from_pretrained("hubentu/cmd2cwl_Llama-3.2-3B")
+tokenizer = AutoTokenizer.from_pretrained("hubentu/cmd2cwl_Llama-3.2-3B")
+model.to('cuda')
+
+text_streamer = TextStreamer(tokenizer)
+_ = model.generate(**inputs, streamer = text_streamer, max_length=8192)
+```
+
+## Using generator
+``` python
+from transformers import pipeline
+generator = pipeline('text-generation', model="checkpoints/cmd2cwl_Llama-3.2-3B", device='cuda')
+resp = generator(question, max_length=8192)
+print(resp[0]['generated_text'].split("### Response:\n")[-1])
+```
+
+## Output
+```
+cwlVersion: v1.0
+class: CommandLineTool
+baseCommand:
+- md5sum
+requirements:
+- class: DockerRequirement
+  dockerPull: alpine:latest
+label: md5sum
+doc: Compute and check MD5 checksums
+inputs:
+  files:
+    label: files
+    doc: Input files
+    type: File[]
+    inputBinding:
+      separate: true
+outputs:
+  md5:
+    label: md5
+    doc: MD5 checksums
+    type: string[]
+    outputBinding:
+      glob: $(inputs.files.name)
+```
+
+
 # Uploaded  model
 
 - **Developed by:** hubentu